Add quantized models with per-model cards, MODELFILE, CLI examples, and auto-upload
Browse files- .gitattributes +9 -0
- MODELFILE +25 -0
- Qwen3-32B-Q2_K/README.md +0 -0
- Qwen3-32B-Q3_K_M/README.md +0 -0
- Qwen3-32B-Q3_K_S/README.md +0 -0
- Qwen3-32B-Q4_K_M/README.md +0 -0
- Qwen3-32B-Q4_K_S/README.md +0 -0
- Qwen3-32B-Q5_K_M/README.md +0 -0
- Qwen3-32B-Q5_K_S/README.md +0 -0
- Qwen3-32B-Q6_K/README.md +0 -0
- Qwen3-32B-Q8_0/README.md +0 -0
- Qwen3-32B-f16_Q2_K.gguf +3 -0
- Qwen3-32B-f16_Q3_K_M.gguf +3 -0
- Qwen3-32B-f16_Q3_K_S.gguf +3 -0
- Qwen3-32B-f16_Q4_K_M.gguf +3 -0
- Qwen3-32B-f16_Q4_K_S.gguf +3 -0
- Qwen3-32B-f16_Q5_K_M.gguf +3 -0
- Qwen3-32B-f16_Q5_K_S.gguf +3 -0
- Qwen3-32B-f16_Q6_K.gguf +3 -0
- Qwen3-32B-f16_Q8_0.gguf +3 -0
- README.md +71 -0
- SHA256SUMS.txt +9 -0
.gitattributes
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@@ -33,3 +33,12 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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MODELFILE
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# MODELFILE for Qwen3-32B-GGUF
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# Used by LM Studio, OpenWebUI, GPT4All, etc.
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context_length: 32768
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embedding: false
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f16: cpu
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# Chat template using ChatML (used by Qwen)
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prompt_template: >-
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<|im_start|>system
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You are a helpful assistant.<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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# Stop sequences help end generation cleanly
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stop: "<|im_end|>"
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stop: "<|im_start|>"
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# Default sampling
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temperature: 0.6
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top_p: 0.95
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top_k: 20
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min_p: 0.0
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repeat_penalty: 1.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:19175fb511c6cf0a387c2a6cc169010d607ddeb146e2ee65295b41386d0fa9f2
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size 12344651648
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version https://git-lfs.github.com/spec/v1
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size 15971777408
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size 14389738368
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version https://git-lfs.github.com/spec/v1
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size 19762149248
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size 18771244928
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oid sha256:733e599a386a8c6b46faed72c1c38563486f94442373350c988f9390c6174b1c
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size 22635493248
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oid sha256:a28f654853d111a029da6d6c39941057f84eae31c54fd405a7953479f290145b
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README.md
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---
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license: apache-2.0
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tags:
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- gguf
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- qwen
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- llama.cpp
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- quantized
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- text-generation
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- reasoning - agent - multilingual
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base_model: Qwen/Qwen3-32B
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author: geoffmunn
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pipeline_tag: text-generation
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language:
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- en
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- zh
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- es
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- fr
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- de
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- ru
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- ar
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- ja
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- ko
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- hi
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---
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# Qwen3-32B-GGUF
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This is a **GGUF-quantized version** of the **[Qwen/Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B)** language model β a **32-billion-parameter** LLM with state-of-the-art reasoning, research capabilities, and enterprise-grade performance. Converted for use with \llama.cpp\, [LM Studio](https://lmstudio.ai), [OpenWebUI](https://openwebui.com), [GPT4All](https://gpt4all.io), and more.
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π‘ **Key Features of Qwen3-32B:**
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π€ **Supports thinking mode** (<think>...</think>) for state-of-the-art math, coding, and logical reasoning.
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π **Dynamically switch** via /think and /no_think in conversation for complex problem solving.
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π§° **Agent-ready**: integrates seamlessly with tools via Qwen-Agent or MCP for enterprise workflows.
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π **Fluent in 100+ languages** including Chinese, English, Arabic, Japanese, Spanish, and more.
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π **State-of-the-art performance** β enterprise-grade reasoning and research capabilities.
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π§ **Cutting-edge reasoning** for advanced research, complex mathematics, and scientific applications.
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πΌ **Enterprise-ready** for professional and academic use cases requiring maximum accuracy.
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## Available Quantizations (from f16)
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| Level | Quality | Speed | Size | Recommendation |
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|----------|--------------|----------|-----------|----------------|
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| Q2_K | Minimal | β‘ Fast | 19.5 GB | Only on severely memory-constrained systems. | | Q3_K_S | Low-Medium | β‘ Fast | 22.2 GB | Minimal viability; avoid unless space-limited. | | Q3_K_M | Low-Medium | β‘ Fast | 23.3 GB | Acceptable for basic interaction. | | Q4_K_S | Practical | β‘ Fast | 27.0 GB | Good balance for mobile/embedded platforms. | | Q4_K_M | Practical | β‘ Fast | 28.1 GB | Best overall choice for most users. | | Q5_K_S | Max Reasoning | π’ Medium | 31.5 GB | Slight quality gain; good for testing. | | Q5_K_M | Max Reasoning | π’ Medium | 32.2 GB | Best quality available. Recommended. | | Q6_K | Near-FP16 | π Slow | 36.5 GB | Diminishing returns. Only if RAM allows. | | Q8_0 | Lossless* | π Slow | 48.0 GB | Maximum fidelity. Ideal for archival. |
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> π‘ **Recommendations by Use Case**
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>
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> - - π’ **Enterprise Workstations (64GB+ RAM)**: Q5_K_M or Q6_K for maximum quality
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- π§ **Advanced Research & Analysis**: Q6_K or Q8_0 for cutting-edge reasoning
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- π¬ **Scientific Computing**: Q6_K for complex mathematical and scientific tasks
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- πΌ **Professional Applications**: Q5_K_M for enterprise-grade accuracy
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- π οΈ **Development & Testing**: Test from Q4_K_M up to Q8_0 based on hardware
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- β οΈ **Note**: Requires substantial RAM (32GB+ recommended for Q5_K_M+)
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## Usage
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Load this model using:
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- [OpenWebUI](https://openwebui.com) β self-hosted AI interface with RAG & tools
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- [LM Studio](https://lmstudio.ai) β desktop app with GPU support
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- [GPT4All](https://gpt4all.io) β private, offline AI chatbot
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- Or directly via \llama.cpp\
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Each quantized model includes its own \README.md\ and shares a common \MODELFILE\.
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## Author
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π€ Geoff Munn (@geoffmunn)
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π [Hugging Face Profile](https://huggingface.co/geoffmunn)
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## Disclaimer
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This is a community conversion for local inference. Not affiliated with Alibaba Cloud or the Qwen team.
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9fc03e1de953be08a62762c3a4f5ab43a3bd138f9ab2498db42ac834a3a38779 Qwen3-32B-f16_Q5_K_M.gguf
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a28f654853d111a029da6d6c39941057f84eae31c54fd405a7953479f290145b Qwen3-32B-f16_Q6_K.gguf
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