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---
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base_model: unsloth/llama-3.3-70b-instruct-bnb-4bit
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library_name: transformers
model_name: outputs
tags:
- generated_from_trainer
- unsloth
- sft
- trl
licence: license
---
# Model Card for outputs
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This model is a fine-tuned version of [unsloth/llama-3.3-70b-instruct-bnb-4bit ](https://huggingface.co/unsloth/llama-3.3-70b-instruct-bnb-4bit ).
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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 = " None " , 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: 0.21.0
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- Transformers: 4.55.4
- Pytorch: 2.8.0
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- Datasets: 3.6.0
- Tokenizers: 0.21.4
## 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 } }
}
```