55 lines
3.2 KiB
Markdown
55 lines
3.2 KiB
Markdown
---
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license: apache-2.0
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language:
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- en
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base_model:
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- prithivMLmods/Magpie-Qwen-DiMind-1.7B
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- text-generation-inference
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- math
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- code
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- reasoning
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---
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# Magpie-Qwen-DiMind-1.7B-GGUF
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> **Magpie-Qwen-DiMind-1.7B** is a compact yet powerful model for **mathematical reasoning**, **code generation**, and **structured output tasks**, built with a dual-intelligence architecture (**DiMind**) to handle both quick-response prompts and deep, multi-step problems. With a parameter size of 1.7B, it balances performance and efficiency, using **80% of the Magpie Pro 330k dataset** and a modular blend of additional datasets for general-purpose and technical tasks.
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## ModelFile
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| File Name | Size | Description |
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| --- | --- | --- |
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| Magpie-Qwen-DiMind-1.7B.BF16.gguf | 3.45 GB | Model file in BF16 format |
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| Magpie-Qwen-DiMind-1.7B.F16.gguf | 3.45 GB | Model file in F16 format |
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| Magpie-Qwen-DiMind-1.7B.F32.gguf | 6.89 GB | Model file in F32 format |
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| Magpie-Qwen-DiMind-1.7B.Q4_K_M.gguf | 1.11 GB | Quantized model file (Q4_K_M) |
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| Magpie-Qwen-DiMind-1.7B.Q5_K_M.gguf | 1.26 GB | Quantized model file (Q5_K_M) |
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| Magpie-Qwen-DiMind-1.7B.Q8_0.gguf | 1.83 GB | Quantized model file (Q8_0) |
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| .gitattributes | 2.01 kB | Git attributes file |
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| README.md | 534 B | Documentation file |
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| config.json | 31 B | Configuration file |
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## Quants Usage
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
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| Link | Type | Size/GB | Notes |
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|:-----|:-----|--------:|:------|
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q2_K.gguf) | Q2_K | 0.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q3_K_S.gguf) | Q3_K_S | 0.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q3_K_M.gguf) | Q3_K_M | 0.5 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q3_K_L.gguf) | Q3_K_L | 0.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.IQ4_XS.gguf) | IQ4_XS | 0.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q4_K_S.gguf) | Q4_K_S | 0.6 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q4_K_M.gguf) | Q4_K_M | 0.6 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q5_K_S.gguf) | Q5_K_S | 0.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q5_K_M.gguf) | Q5_K_M | 0.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q6_K.gguf) | Q6_K | 0.7 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q8_0.gguf) | Q8_0 | 0.9 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.f16.gguf) | f16 | 1.6 | 16 bpw, overkill |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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types (lower is better):
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