Regulus-Qwen3-R1-Llama-Distill-GGUF/README.md

license, datasets, language, base_model, pipeline_tag, library_name, tags

license	datasets	language	base_model	pipeline_tag	library_name	tags
apache-2.0	Magpie-Align/Magpie-Reasoning-V2-250K-CoT-Deepseek-R1-Llama-70B	en	prithivMLmods/Regulus-Qwen3-R1-Llama-Distill-1.7B	text-generation	transformers	text-generation-inference trl reasoning code math

Regulus-Qwen3-R1-Llama-Distill-GGUF

Regulus-Qwen3-R1-Llama-Distill-1.7B is a distilled reasoning model fine-tuned on Qwen/Qwen3-1.7B using Magpie-Align/Magpie-Reasoning-V2-250K-CoT-DeepSeek-R1-Llama-70B. The training leverages distilled traces from DeepSeek-R1-Llama-70B, transferring advanced reasoning patterns into a lightweight 1.7B parameter model. It is specialized for chain-of-thought reasoning across code, math, and science, optimized for efficiency and mid-resource deployment.

Model Files

File Name	Quant Type	File Size
Regulus-Qwen3-R1-Llama-Distill-1.7B.BF16.gguf	BF16	3.45 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.F16.gguf	F16	3.45 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.F32.gguf	F32	6.89 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q2_K.gguf	Q2_K	778 MB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q3_K_L.gguf	Q3_K_L	1 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q3_K_M.gguf	Q3_K_M	940 MB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q3_K_S.gguf	Q3_K_S	867 MB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q4_0.gguf	Q4_0	1.05 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q4_1.gguf	Q4_1	1.14 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q4_K.gguf	Q4_K	1.11 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q4_K_M.gguf	Q4_K_M	1.11 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q4_K_S.gguf	Q4_K_S	1.06 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q5_0.gguf	Q5_0	1.23 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q5_1.gguf	Q5_1	1.32 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q5_K.gguf	Q5_K	1.26 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q5_K_M.gguf	Q5_K_M	1.26 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q5_K_S.gguf	Q5_K_S	1.23 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q6_K.gguf	Q6_K	1.42 GB
Regulus-Qwen3-R1-Llama-Distill-1.7B.Q8_0.gguf	Q8_0	1.83 GB

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):