BrainCog-8B-0.1-Instruct

3

8.0B

3 languages

llama

by

sunbaby

Language Model

OTHER

8B params

New

3 downloads

Early-stage

Try on Hugging Face Add to Compare

Edge AI:

Mobile

Laptop

Server

18GB+ RAM

Mobile

Laptop

Server

Quick Summary

Responsibility The output of the model is uncontrollable, and its output does not represent our opinion

Device Compatibility

Mobile

4-6GB RAM

Laptop

16GB RAM

Server

GPU

Minimum Recommended

8GB+ RAM

Code Examples

Model Informationpythontransformers

import torch
import transformers

model_id = "sunbaby/BrainCog-8B-0.1-Instruct"
pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={
      "torch_dtype": torch.bfloat16
    },
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a useful chatbot or assistant to help people."},
    {"role": "user", "content": "How are you?"},
]
outputs = pipeline(
    messages,
    max_new_tokens=2048,
)
print(outputs[0]["generated_text"][-1])

Model Informationpythontransformers

import torch
import transformers

model_id = "sunbaby/BrainCog-8B-0.1-Instruct"
pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={
      "torch_dtype": torch.bfloat16
    },
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a useful chatbot or assistant to help people."},
    {"role": "user", "content": "How are you?"},
]
outputs = pipeline(
    messages,
    max_new_tokens=2048,
)
print(outputs[0]["generated_text"][-1])

Model Informationpythontransformers

import torch
import transformers

model_id = "sunbaby/BrainCog-8B-0.1-Instruct"
pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={
      "torch_dtype": torch.bfloat16
    },
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a useful chatbot or assistant to help people."},
    {"role": "user", "content": "How are you?"},
]
outputs = pipeline(
    messages,
    max_new_tokens=2048,
)
print(outputs[0]["generated_text"][-1])

Model Informationpythontransformers

import torch
import transformers

model_id = "sunbaby/BrainCog-8B-0.1-Instruct"
pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={
      "torch_dtype": torch.bfloat16
    },
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a useful chatbot or assistant to help people."},
    {"role": "user", "content": "How are you?"},
]
outputs = pipeline(
    messages,
    max_new_tokens=2048,
)
print(outputs[0]["generated_text"][-1])

Model Informationpythontransformers

import torch
import transformers

model_id = "sunbaby/BrainCog-8B-0.1-Instruct"
pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={
      "torch_dtype": torch.bfloat16
    },
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a useful chatbot or assistant to help people."},
    {"role": "user", "content": "How are you?"},
]
outputs = pipeline(
    messages,
    max_new_tokens=2048,
)
print(outputs[0]["generated_text"][-1])

Model Informationpythontransformers

import torch
import transformers

model_id = "sunbaby/BrainCog-8B-0.1-Instruct"
pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={
      "torch_dtype": torch.bfloat16
    },
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a useful chatbot or assistant to help people."},
    {"role": "user", "content": "How are you?"},
]
outputs = pipeline(
    messages,
    max_new_tokens=2048,
)
print(outputs[0]["generated_text"][-1])

Model Informationpythontransformers

import torch
import transformers

model_id = "sunbaby/BrainCog-8B-0.1-Instruct"
pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={
      "torch_dtype": torch.bfloat16
    },
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a useful chatbot or assistant to help people."},
    {"role": "user", "content": "How are you?"},
]
outputs = pipeline(
    messages,
    max_new_tokens=2048,
)
print(outputs[0]["generated_text"][-1])

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