ARES-Nano-9.5-Conversational

1
license:mit
by
AresAGI
Language Model
OTHER
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Quick Summary

AI model with specialized capabilities.

Code Examples

🚀 Como usarpythontransformers
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

tokenizer = AutoTokenizer.from_pretrained("AresAGI/ARES-Nano-SLM-Conversational")
model = AutoModelForCausalLM.from_pretrained("AresAGI/ARES-Nano-SLM-Conversational")

prompt = "<|im_start|>user\noi ares<|im_end|>\n<|im_start|>assistant\n"
inputs = tokenizer(prompt, return_tensors="pt")

with torch.no_grad():
    outputs = model.generate(
        **inputs,
        max_new_tokens=50,
        temperature=0.7,
        do_sample=True,
        repetition_penalty=1.3
    )

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

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