CoolFace
Modelpublic

prithivMLmods/Luth-Instruct-GGUF

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
1likes1.4kdownloads
Model Card

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 NameModel SizeDownload Link
Luth-1.7B-Instruct-GGUF1.7BHugging Face
Luth-0.6B-Instruct-GGUF0.6BHugging Face

Model Files

Luth-1.7B-Instruct

File NameQuant TypeFile Size
Luth-1.7B-Instruct.BF16.ggufBF163.45 GB
Luth-1.7B-Instruct.F16.ggufF163.45 GB
Luth-1.7B-Instruct.F32.ggufF326.89 GB
Luth-1.7B-Instruct.Q2_K.ggufQ2_K778 MB
Luth-1.7B-Instruct.Q3KL.ggufQ3KL1 GB
Luth-1.7B-Instruct.Q3KM.ggufQ3KM940 MB
Luth-1.7B-Instruct.Q3KS.ggufQ3KS867 MB
Luth-1.7B-Instruct.Q4_0.ggufQ4_01.05 GB
Luth-1.7B-Instruct.Q4_1.ggufQ4_11.14 GB
Luth-1.7B-Instruct.Q4_K.ggufQ4_K1.11 GB
Luth-1.7B-Instruct.Q4KM.ggufQ4KM1.11 GB
Luth-1.7B-Instruct.Q4KS.ggufQ4KS1.06 GB
Luth-1.7B-Instruct.Q5_0.ggufQ5_01.23 GB
Luth-1.7B-Instruct.Q5_1.ggufQ5_11.32 GB
Luth-1.7B-Instruct.Q5_K.ggufQ5_K1.26 GB
Luth-1.7B-Instruct.Q5KM.ggufQ5KM1.26 GB
Luth-1.7B-Instruct.Q5KS.ggufQ5KS1.23 GB
Luth-1.7B-Instruct.Q6_K.ggufQ6_K1.42 GB
Luth-1.7B-Instruct.Q8_0.ggufQ8_01.83 GB

Luth-0.6B-Instruct

File NameQuant TypeFile Size
Luth-0.6B-Instruct.BF16.ggufBF161.2 GB
Luth-0.6B-Instruct.F16.ggufF161.2 GB
Luth-0.6B-Instruct.F32.ggufF322.39 GB
Luth-0.6B-Instruct.Q2_K.ggufQ2_K296 MB
Luth-0.6B-Instruct.Q3KL.ggufQ3KL368 MB
Luth-0.6B-Instruct.Q3KM.ggufQ3KM347 MB
Luth-0.6B-Instruct.Q3KS.ggufQ3KS323 MB
Luth-0.6B-Instruct.Q4_0.ggufQ4_0382 MB
Luth-0.6B-Instruct.Q4_1.ggufQ4_1409 MB
Luth-0.6B-Instruct.Q4_K.ggufQ4_K397 MB
Luth-0.6B-Instruct.Q4KM.ggufQ4KM397 MB
Luth-0.6B-Instruct.Q4KS.ggufQ4KS383 MB
Luth-0.6B-Instruct.Q5_0.ggufQ5_0437 MB
Luth-0.6B-Instruct.Q5_1.ggufQ5_1464 MB
Luth-0.6B-Instruct.Q5_K.ggufQ5_K444 MB
Luth-0.6B-Instruct.Q5KM.ggufQ5KM444 MB
Luth-0.6B-Instruct.Q5KS.ggufQ5KS437 MB
Luth-0.6B-Instruct.Q6_K.ggufQ6_K495 MB
Luth-0.6B-Instruct.Q8_0.ggufQ8_0639 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