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---
license: apache-2.0
datasets:
- gair-prox/FineWeb-pro
language:
- en
tags:
- llama
pipeline_tag: text-generation
library_name: transformers
---
[](https://hf.co/QuantFactory)
# QuantFactory/FW-ProX-1.7B-GGUF
This is quantized version of [gair-prox/FW-ProX-1.7B](https://huggingface.co./gair-prox/FW-ProX-1.7B) created using llama.cpp
# Original Model Card
# FW-ProX-1.7B
<p align="center">
<img src="prox-teaser.png">
</p>
[ArXiv](https://arxiv.org/abs/2409.17115) | [Models](https://huggingface.co./gair-prox/FW-ProX-1.7B) | [Data](https://huggingface.co./datasets/gair-prox/FineWeb-pro) | [Code](https://github.com/GAIR-NLP/program-every-example)
**FW-ProX-1.7B** is a small language model. It was and trained on the [FineWeb-pro](https://huggingface.co./datasets/gair-prox/FineWeb-pro) for 50B tokens.
## Evaluations
ProX models are evaluated over 10 language model benchmarks in zero-shot setting.
| | ArC-c | ARC-e | CSQA | HellaS | MMLU | OBQA | PiQA | SIQA | WinoG | SciQ | AVG |
|-----------------------|-------|-------|-------|-----------|-------|-------|-------|-------|-------|-------|------|
| raw | 28.5 | 52.6 | 33.9 | 53.2 | 29.8 | 32.6 | 72.9 | 40.2 | 53.0 | 77.1 | 47.4 |
| ours | 34.4 | 63.9 | 32.6 | 53.0 | 33.1 | 34.4 | 73.1 | 39.3 | 52.7 | 81.5 | 49.8 |
### Citation
```
@article{zhou2024programming,
title={Programming Every Example: Lifting Pre-training Data Quality like Experts at Scale},
author={Zhou, Fan and Wang, Zengzhi and Liu, Qian and Li, Junlong and Liu, Pengfei},
journal={arXiv preprint arXiv:2409.17115},
year={2024}
}
```
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