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

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

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

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:

@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}}
}