🍷 FineLlama-3.1-8B

This is a finetune of meta-llama/Meta-Llama-3.1-8B made for my Hands on Learnings "Fine-tune Llama 3.1 Ultra-Efficiently with Unsloth".

It was trained on 100k super high-quality samples from the mlabonne/FineTome-100k dataset.

Try the demo: https://huggingface.co/spaces/Karthick1002/FineLlama-3.1-8B

🔎 Applications

This model was made for My Pratice Puropose I recommend using Meta's instruct model for real applications.

🏆 Evaluation

TBD.

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Karthick1002/FineLlama-3.1-8B"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])

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This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.