--- base_model: codellama/CodeLlama-7b-hf library_name: transformers model_name: outputs tags: - generated_from_trainer - sft - trl licence: license --- # Model Card for outputs This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python import torch from transformers import pipeline, AutoTokenizer question = "Write a Python function that takes a list of numbers and returns the list sorted in ascending order without using the built-in `sorted()` function. Return ONLY code in your output. ###Python code:" generator = pipeline("text-generation", model="mariasandu/python-coding-assistant-v2", device="cuda") tokenizer = AutoTokenizer.from_pretrained("mariasandu/python-coding-assistant-v2") tokenizer.chat_template = "{% for message in messages %}{% if message['role'] == 'user' %}[INST] {{ message['content'] }} [/INST]{% else %}{{ message['content'] }}{% endif %}{% endfor %}" output = generator(question)[0] print(output['generated_text']) ``` ## Training procedure [Visualize in Weights & Biases](https://wandb.ai/mos7589-prompt-inversion/huggingface/runs/a1be6dcy) This model was trained with SFT. ### Framework versions - TRL: 0.25.1 - Transformers: 4.57.1 - Pytorch: 2.8.0+cu126 - Datasets: 4.0.0 - Tokenizers: 0.22.1 ## 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 Gallou{\'e}dec}, year = 2020, journal = {GitHub repository}, publisher = {GitHub}, howpublished = {\url{https://github.com/huggingface/trl}} } ```