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llama-sft/README.md
ModelHub XC 1f1cbca5b3 初始化项目,由ModelHub XC社区提供模型
Model: sampluralis/llama-sft
Source: Original Platform
2026-05-08 23:31:07 +08:00

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---
library_name: transformers
model_name: llama-sft
tags:
- generated_from_trainer
- sft
- trl
licence: license
---
# Model Card for llama-sft
This model is a fine-tuned version of [None](https://huggingface.co/None).
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="sampluralis/llama-sft", 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"/>](https://wandb.ai/ajanthan-pluralis-research/huggingface/runs/1m05mync)
This model was trained with SFT.
### Framework versions
- TRL: 0.28.0
- Transformers: 4.57.6
- Pytorch: 2.6.0+cu126
- Datasets: 4.6.1
- Tokenizers: 0.22.2
## Citations
Cite TRL as:
```bibtex
@software{vonwerra2020trl,
title = {{TRL: Transformers Reinforcement Learning}},
author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
license = {Apache-2.0},
url = {https://github.com/huggingface/trl},
year = {2020}
}
```