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Model: prithivMLmods/Magpie-Qwen-DiMind-1.7B-GGUF
Source: Original Platform

Magpie-Qwen-DiMind-1.7B.BF16.gguf

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Magpie-Qwen-DiMind-1.7B.F16.gguf

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+size 3447349408

Magpie-Qwen-DiMind-1.7B.F32.gguf

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Magpie-Qwen-DiMind-1.7B.Q4_K_M.gguf

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Magpie-Qwen-DiMind-1.7B.Q5_K_M.gguf

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Magpie-Qwen-DiMind-1.7B.Q8_0.gguf

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+size 1834426528

.gitattributes

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README.md

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+---
+license: apache-2.0
+language:
+- en
+base_model:
+- prithivMLmods/Magpie-Qwen-DiMind-1.7B
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- text-generation-inference
+- math
+- code
+- reasoning
+---
+# Magpie-Qwen-DiMind-1.7B-GGUF
+
+> **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.
+
+## ModelFile
+
+| File Name | Size | Description |
+| --- | --- | --- |
+| Magpie-Qwen-DiMind-1.7B.BF16.gguf | 3.45 GB | Model file in BF16 format |
+| Magpie-Qwen-DiMind-1.7B.F16.gguf | 3.45 GB | Model file in F16 format |
+| Magpie-Qwen-DiMind-1.7B.F32.gguf | 6.89 GB | Model file in F32 format |
+| Magpie-Qwen-DiMind-1.7B.Q4_K_M.gguf | 1.11 GB | Quantized model file (Q4_K_M) |
+| Magpie-Qwen-DiMind-1.7B.Q5_K_M.gguf | 1.26 GB | Quantized model file (Q5_K_M) |
+| Magpie-Qwen-DiMind-1.7B.Q8_0.gguf | 1.83 GB | Quantized model file (Q8_0) |
+| .gitattributes | 2.01 kB | Git attributes file |
+| README.md | 534 B | Documentation file |
+| config.json | 31 B | Configuration file |
+
+## Quants Usage 
+
+(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
+
+| Link | Type | Size/GB | Notes |
+|:-----|:-----|--------:|:------|
+| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q2_K.gguf) | Q2_K | 0.4 |  |
+| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q3_K_S.gguf) | Q3_K_S | 0.5 |  |
+| [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 |
+| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q3_K_L.gguf) | Q3_K_L | 0.5 |  |
+| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.IQ4_XS.gguf) | IQ4_XS | 0.6 |  |
+| [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 |
+| [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 |
+| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q5_K_S.gguf) | Q5_K_S | 0.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q5_K_M.gguf) | Q5_K_M | 0.7 |  |
+| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q6_K.gguf) | Q6_K | 0.7 | very good quality |
+| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q8_0.gguf) | Q8_0 | 0.9 | fast, best quality |
+| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.f16.gguf) | f16 | 1.6 | 16 bpw, overkill |
+
+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": "text-generation", "allow_remote": true}