Llama3.1_CoT_V1

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llama

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xinchen9

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Quick Summary

AI model with specialized capabilities.

Training Data Analysis

🔵 Good (6.0/10)

Researched training datasets used by Llama3.1_CoT_V1 with quality assessment

Specialized For

general

multilingual

Training Datasets (1)

🔵 6/10

general

multilingual

Key Strengths

•Scale and Accessibility: 750GB of publicly available, filtered text
•Systematic Filtering: Documented heuristics enable reproducibility
•Language Diversity: Despite English-only, captures diverse writing styles

Considerations

•English-Only: Limits multilingual applications
•Filtering Limitations: Offensive content and low-quality text remain despite filtering

Explore our comprehensive training dataset analysis

View All Datasets

Code Examples

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

2. How to Usepythontransformers

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name = "xinchen9/Llama3.1_CoT_V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
model.generation_config = GenerationConfig.from_pretrained(model_name)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

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