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README.md

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+
+---
+
+license: apache-2.0
+datasets:
+- gair-prox/FineWeb-pro
+language:
+- en
+tags:
+- llama
+pipeline_tag: text-generation
+library_name: transformers
+
+---
+
+[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](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}
+}
+```