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Model: prithivMLmods/Nenque-MoT-0.6B-Elite14-GGUF
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+language:
+- en
+base_model:
+- prithivMLmods/Nenque-MoT-0.6B-Elite14
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- text-generation-inference
+- math
+- thinking
+---
+
+# **Nenque-MoT-0.6B-Elite14-GGUF**
+
+> **Nenque-MoT-0.6B-Elite14** is a compact, high-efficiency model tailored for **mathematical reasoning**, **code generation**, and **structured technical inference**. Fine-tuned from **Qwen3-0.6B** using the **MoT (Mixture of Thoughts) dataset**—with a focus on **math expert clusters**—this model delivers strong symbolic performance in low-resource environments. Despite its **0.6B parameter** size, it offers elite-level precision across STEM and multilingual technical domains.
+
+## Model File
+
+| File Name                                   | Size   | Format        | Description                             |
+|--------------------------------------------|--------|---------------|-----------------------------------------|
+| Nenque-MoT-0.6B-Elite14.BF16.gguf          | 1.2 GB | GGUF (BF16)   | BFloat16 precision model file           |
+| Nenque-MoT-0.6B-Elite14.F16.gguf           | 1.2 GB | GGUF (F16)    | Float16 precision model file            |
+| Nenque-MoT-0.6B-Elite14.Q4_K_M.gguf        | 397 MB | GGUF (Q4_K_M) | 4-bit quantized model file              |
+| Nenque-MoT-0.6B-Elite14.Q5_K_M.gguf        | 444 MB | GGUF (Q5_K_M) | 5-bit quantized model file              |
+| unsloth.Q8_0.gguf                          | 639 MB | GGUF (Q8_0)   | 8-bit quantized model file              |
+| config.json                                | 31 B   | JSON          | Configuration file                      |
+| .gitattributes                             | 1.86 kB| Text          | Git attributes configuration            |
+
+## 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}