初始化项目，由ModelHub XC社区提供模型

Model: unsloth/Jan-nano-GGUF
Source: Original Platform

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README.md

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+---
+tags:
+- unsloth
+license: apache-2.0
+base_model:
+- Menlo/Jan-nano
+pipeline_tag: text-generation
+---
+<div>
+<p style="margin-top: 0;margin-bottom: 0;">
+    <em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
+  </p>
+  <div style="display: flex; gap: 5px; align-items: center; ">
+    <a href="https://github.com/unslothai/unsloth/">
+      <img src="https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png" width="133">
+    </a>
+    <a href="https://discord.gg/unsloth">
+      <img src="https://github.com/unslothai/unsloth/raw/main/images/Discord%20button.png" width="173">
+    </a>
+    <a href="https://docs.unsloth.ai/basics/qwen3-how-to-run-and-fine-tune">
+      <img src="https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/images/documentation%20green%20button.png" width="143">
+    </a>
+  </div>
+</div>
+
+# Jan-Nano: A 4B MCP-Optimized DeepResearch Model
+[![GitHub](https://img.shields.io/badge/GitHub-Repository-blue?logo=github)](https://github.com/menloresearch/deep-research) 
+
+<div align="center">
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/65713d70f56f9538679e5a56/wC7Xtolp7HOFIdKTOJhVt.png" width="300" alt="Jan-Nano">
+</div>
+
+## Overview
+
+Jan-Nano is a compact 4-billion parameter language model specifically designed and trained for deep research tasks. This model has been optimized to work seamlessly with Model Context Protocol (MCP) servers, enabling efficient integration with various research tools and data sources.
+
+## Evaluation
+Jan-Nano has been evaluated on the SimpleQA benchmark using our MCP-based benchmark methodology, demonstrating strong performance for its model size:
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65713d70f56f9538679e5a56/sdRfF9FX5ApPow9gZ31No.png)
+
+The evaluation was conducted using our MCP-based benchmark approach, which assesses the model's performance on SimpleQA tasks while leveraging its native MCP server integration capabilities. This methodology better reflects Jan-Nano's real-world performance as a tool-augmented research model, validating both its factual accuracy and its effectiveness in MCP-enabled environments.
+
+## How to Run Locally
+
+![Jan-Nano Demo](replay.gif)
+
+Jan-Nano is supported by [Jan]((https://github.com/menloresearch/jan)), an open-source ChatGPT alternative that runs entirely on your computer. Jan provides a user-friendly interface for running local AI models with full privacy and control.

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}