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| Name | Quant method | Size |
|---|---|---|
| math-chunk-refining-lm.Q2_K.gguf | Q2_K | 0.14GB |
| math-chunk-refining-lm.IQ3_XS.gguf | IQ3_XS | 0.15GB |
| math-chunk-refining-lm.IQ3_S.gguf | IQ3_S | 0.16GB |
| math-chunk-refining-lm.Q3_K_S.gguf | Q3_K_S | 0.16GB |
| math-chunk-refining-lm.IQ3_M.gguf | IQ3_M | 0.16GB |
| math-chunk-refining-lm.Q3_K.gguf | Q3_K | 0.17GB |
| math-chunk-refining-lm.Q3_K_M.gguf | Q3_K_M | 0.17GB |
| math-chunk-refining-lm.Q3_K_L.gguf | Q3_K_L | 0.18GB |
| math-chunk-refining-lm.IQ4_XS.gguf | IQ4_XS | 0.19GB |
| math-chunk-refining-lm.Q4_0.gguf | Q4_0 | 0.2GB |
| math-chunk-refining-lm.IQ4_NL.gguf | IQ4_NL | 0.2GB |
| math-chunk-refining-lm.Q4_K_S.gguf | Q4_K_S | 0.2GB |
| math-chunk-refining-lm.Q4_K.gguf | Q4_K | 0.2GB |
| math-chunk-refining-lm.Q4_K_M.gguf | Q4_K_M | 0.2GB |
| math-chunk-refining-lm.Q4_1.gguf | Q4_1 | 0.21GB |
| math-chunk-refining-lm.Q5_0.gguf | Q5_0 | 0.23GB |
| math-chunk-refining-lm.Q5_K_S.gguf | Q5_K_S | 0.23GB |
| math-chunk-refining-lm.Q5_K.gguf | Q5_K | 0.24GB |
| math-chunk-refining-lm.Q5_K_M.gguf | Q5_K_M | 0.24GB |
| math-chunk-refining-lm.Q5_1.gguf | Q5_1 | 0.25GB |
| math-chunk-refining-lm.Q6_K.gguf | Q6_K | 0.27GB |
| math-chunk-refining-lm.Q8_0.gguf | Q8_0 | 0.35GB |
@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}
}