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FYPFAST/Llama-3.2-3B-Instruct-PEP8-Vulnerability-Python

sourceHugging Faceupdated 2y agoView on Hugging Face
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Model Card for Llama-3.2-8B-Instruct-PEP8-Vulnerability-Python

This model is a fine-tuned version of unsloth/llama-3.2-3b-instruct-bnb-4bit. It has been trained using TRL.

Quick start

python
from transformers import pipeline

question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="FYPFAST/Llama-3.2-8B-Instruct-PEP8-Vulnerability-Python", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

Training procedure

<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>

This model was trained with SFT.

Framework versions

  • TRL: 0.13.0
  • Transformers: 4.47.1
  • Pytorch: 2.5.1+cu121
  • Datasets: 3.2.0
  • Tokenizers: 0.21.0

Tags


tags:

  • text-generation
  • code-generation
  • causal-lm ---

Citations

Cite TRL as:

bibtex
@misc{vonwerra2022trl,
	title        = {{TRL: Transformer Reinforcement Learning}},
	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
	year         = 2020,
	journal      = {GitHub repository},
	publisher    = {GitHub},
	howpublished = {\url{https://github.com/huggingface/trl}}
}