commit beb61f6df9893efe420e4f54ba272c8cb4519c14 Author: ModelHub XC Date: Thu Oct 22 14:48:13 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: prithivMLmods/Luth-Instruct-GGUF Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..53d7257 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,47 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bin.* filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text 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+tags: +- text-generation-inference +--- + +# **Luth-Instruct-GGUF** + +> Luth-1.7B-Instruct is a French fine-tuned variant of the Qwen3-1.7B model, enhanced using the Luth-SFT dataset to significantly improve its capabilities in French instruction following, mathematics, and general knowledge while maintaining and even boosting its English performance. It was trained by full fine-tuning with Axolotl and later merged with the base Qwen3-1.7B, thus preserving its English competencies alongside marked improvements in French benchmarks. The model demonstrates strong performance on selected French and English benchmarks, including ifeval, gpqa-diamond, mmlu, math-500, arc-chall, and hellaswag, showing notable gains over comparable models in both languages. It is designed for tasks requiring bilingual proficiency with pronounced strength in French and is supported by available evaluation, training, and data scripts on GitHub. The model is suitable for instruction-following applications in contexts demanding enhanced French language understanding without compromising English language capabilities. It is openly accessible under an appropriate license for research and usage. + +| Model Name | Model Size | Download Link | +|------------|------|---------------| +| **Luth-1.7B-Instruct-GGUF** | 1.7B | [Hugging Face](https://huggingface.co/prithivMLmods/Luth-Instruct-GGUF/tree/main/Luth-1.7B-Instruct-GGUF) | +| **Luth-0.6B-Instruct-GGUF** | 0.6B | [Hugging Face](https://huggingface.co/prithivMLmods/Luth-Instruct-GGUF/tree/main/Luth-0.6B-Instruct-GGUF) | + +## Model Files + +### Luth-1.7B-Instruct + +| File Name | Quant Type | File Size | +| - | - | - | +| Luth-1.7B-Instruct.BF16.gguf | BF16 | 3.45 GB | +| Luth-1.7B-Instruct.F16.gguf | F16 | 3.45 GB | +| Luth-1.7B-Instruct.F32.gguf | F32 | 6.89 GB | +| Luth-1.7B-Instruct.Q2_K.gguf | Q2_K | 778 MB | +| Luth-1.7B-Instruct.Q3_K_L.gguf | Q3_K_L | 1 GB | +| Luth-1.7B-Instruct.Q3_K_M.gguf | Q3_K_M | 940 MB | +| Luth-1.7B-Instruct.Q3_K_S.gguf | Q3_K_S | 867 MB | +| Luth-1.7B-Instruct.Q4_0.gguf | Q4_0 | 1.05 GB | +| Luth-1.7B-Instruct.Q4_1.gguf | Q4_1 | 1.14 GB | +| Luth-1.7B-Instruct.Q4_K.gguf | Q4_K | 1.11 GB | +| Luth-1.7B-Instruct.Q4_K_M.gguf | Q4_K_M | 1.11 GB | +| Luth-1.7B-Instruct.Q4_K_S.gguf | Q4_K_S | 1.06 GB | +| Luth-1.7B-Instruct.Q5_0.gguf | Q5_0 | 1.23 GB | +| Luth-1.7B-Instruct.Q5_1.gguf | Q5_1 | 1.32 GB | +| Luth-1.7B-Instruct.Q5_K.gguf | Q5_K | 1.26 GB | +| Luth-1.7B-Instruct.Q5_K_M.gguf | Q5_K_M | 1.26 GB | +| Luth-1.7B-Instruct.Q5_K_S.gguf | Q5_K_S | 1.23 GB | +| Luth-1.7B-Instruct.Q6_K.gguf | Q6_K | 1.42 GB | +| Luth-1.7B-Instruct.Q8_0.gguf | Q8_0 | 1.83 GB | + +### Luth-0.6B-Instruct + +| File Name | Quant Type | File Size | +| - | - | - | +| Luth-0.6B-Instruct.BF16.gguf | BF16 | 1.2 GB | +| Luth-0.6B-Instruct.F16.gguf | F16 | 1.2 GB | +| Luth-0.6B-Instruct.F32.gguf | F32 | 2.39 GB | +| Luth-0.6B-Instruct.Q2_K.gguf | Q2_K | 296 MB | +| Luth-0.6B-Instruct.Q3_K_L.gguf | Q3_K_L | 368 MB | +| Luth-0.6B-Instruct.Q3_K_M.gguf | Q3_K_M | 347 MB | +| Luth-0.6B-Instruct.Q3_K_S.gguf | Q3_K_S | 323 MB | +| Luth-0.6B-Instruct.Q4_0.gguf | Q4_0 | 382 MB | +| Luth-0.6B-Instruct.Q4_1.gguf | Q4_1 | 409 MB | +| Luth-0.6B-Instruct.Q4_K.gguf | Q4_K | 397 MB | +| Luth-0.6B-Instruct.Q4_K_M.gguf | Q4_K_M | 397 MB | +| Luth-0.6B-Instruct.Q4_K_S.gguf | Q4_K_S | 383 MB | +| Luth-0.6B-Instruct.Q5_0.gguf | Q5_0 | 437 MB | +| Luth-0.6B-Instruct.Q5_1.gguf | Q5_1 | 464 MB | +| Luth-0.6B-Instruct.Q5_K.gguf | Q5_K | 444 MB | +| Luth-0.6B-Instruct.Q5_K_M.gguf | Q5_K_M | 444 MB | +| Luth-0.6B-Instruct.Q5_K_S.gguf | Q5_K_S | 437 MB | +| Luth-0.6B-Instruct.Q6_K.gguf | Q6_K | 495 MB | +| Luth-0.6B-Instruct.Q8_0.gguf | Q8_0 | 639 MB | + +## Quants Usage + +(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) + +Here is a handy graph by ikawrakow comparing some lower-quality quant +types (lower is better): + +![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) diff --git a/configuration.json b/configuration.json new file mode 100644 index 0000000..bbeeda1 --- /dev/null +++ b/configuration.json @@ -0,0 +1 @@ +{"framework": "pytorch", "task": "text-generation", "allow_remote": true} \ No newline at end of file