safetensors region:us
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Quantization made by Richard Erkhov.

[Github](https://github.com/RichardErkhov)

[Discord](https://discord.gg/pvy7H8DZMG)

[Request more models](https://github.com/RichardErkhov/quant_request)


Phi-3.5-mini-instruct_loraft_translation-eval - bnb 4bits
- Model creator: https://huggingface.co/garygao2000/
- Original model: https://huggingface.co/garygao2000/Phi-3.5-mini-instruct_loraft_translation-eval/




Original model description:
---
base_model: microsoft/Phi-3.5-mini-instruct
library_name: transformers
model_name: Phi-3.5-mini-instruct_loraft_translation-eval
tags:
- generated_from_trainer
- trl
- sft
licence: license
---

# Model Card for Phi-3.5-mini-instruct_loraft_translation-eval

This model is a fine-tuned version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-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="garygao2000/Phi-3.5-mini-instruct_loraft_translation-eval", 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/garygao2000-personal/finetune-llm-for-datafix/runs/7269211554.27110-c31775d1-e752-4d2b-832f-921a0fb2612d)

This model was trained with SFT.

### Framework versions

- TRL: 0.12.0
- Transformers: 4.46.1
- Pytorch: 2.5.1
- Datasets: 3.1.0
- Tokenizers: 0.20.1

## 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 Gallouédec},
	year         = 2020,
	journal      = {GitHub repository},
	publisher    = {GitHub},
	howpublished = {\url{https://github.com/huggingface/trl}}
}
```

