base_model: unsloth/Meta-Llama-3.1-8B-Instruct | |
library_name: transformers | |
model_name: outputs | |
tags: | |
- generated_from_trainer | |
- unsloth | |
- trl | |
- sft | |
licence: license | |
# Model Card for outputs | |
This model is a fine-tuned version of [unsloth/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct). | |
It has been trained using [TRL](https://github.com/huggingface/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="armanibadboy/outputs", 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 | |
## 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}} | |
} | |
``` |