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Model: prithivMLmods/rStar-Coder-Qwen3-0.6B-GGUF
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+language:
+- en
+base_model:
+- prithivMLmods/rStar-Coder-Qwen3-0.6B
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- text-generation-inference
+---
+
+# **rStar-Coder-Qwen3-0.6B-GGUF**
+
+> rStar-Coder-Qwen3-0.6B is a compact, multi-domain language model fine-tuned from Qwen-0.6B using the rStar-Coder dataset, which incorporates code expert clusters and an extended symbolic reasoning collection; it excels at unified reasoning across code, mathematics, and science, delivering advanced code generation, algorithm synthesis, multi-language error detection, and step-by-step scientific problem-solving, while supporting structured output in LaTeX, Markdown, JSON, CSV, and YAML—making it ideal for developers, educators, and researchers requiring efficient STEM-oriented AI on mid-range GPUs, offline clusters, and edge devices, with a focus on logic-driven responses and technical data generation rather than general chat or creative writing.
+
+# Model Files
+
+| File Name | Size | Quant Type |
+|-----------|------|------------|
+| rStar-Coder-Qwen3-0.6B.BF16.gguf | 1.2 GB | BF16 |
+| rStar-Coder-Qwen3-0.6B.F16.gguf | 1.2 GB | F16 |
+| rStar-Coder-Qwen3-0.6B.F32.gguf | 2.39 GB | F32 |
+| rStar-Coder-Qwen3-0.6B.Q2_K.gguf | 296 MB | Q2_K |
+| rStar-Coder-Qwen3-0.6B.Q3_K_L.gguf | 368 MB | Q3_K_L |
+| rStar-Coder-Qwen3-0.6B.Q3_K_M.gguf | 347 MB | Q3_K_M |
+| rStar-Coder-Qwen3-0.6B.Q3_K_S.gguf | 323 MB | Q3_K_S |
+| rStar-Coder-Qwen3-0.6B.Q4_K_M.gguf | 397 MB | Q4_K_M |
+| rStar-Coder-Qwen3-0.6B.Q4_K_S.gguf | 383 MB | Q4_K_S |
+| rStar-Coder-Qwen3-0.6B.Q5_K_M.gguf | 444 MB | Q5_K_M |
+| rStar-Coder-Qwen3-0.6B.Q5_K_S.gguf | 437 MB | Q5_K_S |
+| rStar-Coder-Qwen3-0.6B.Q6_K.gguf | 495 MB | Q6_K |
+| rStar-Coder-Qwen3-0.6B.Q8_0.gguf | 639 MB | Q8_0 |
+
+## 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)

config.json

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+{
+    "model_type": "qwen3"
+}

configuration.json

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+{"framework": "pytorch", "task": "others", "allow_remote": true}

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