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Model: unsloth/Jan-nano-128k-GGUF
Source: Original Platform

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README.md

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+---
+tags:
+- unsloth
+license: apache-2.0
+language:
+- en
+base_model:
+- Menlo/Jan-nano-128k
+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-128k: Empowering deeper research through extended context understanding.
+
+[![GitHub](https://img.shields.io/badge/GitHub-Repository-blue?logo=github)](https://github.com/menloresearch/deep-research) 
+[![Context Length](https://img.shields.io/badge/Context-128k-green)](https://huggingface.co/Menlo/Jan-nano-128k)
+[![License](https://img.shields.io/badge/License-Apache%202.0-yellow)](https://opensource.org/licenses/Apache-2.0)
+
+<div align="center">
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/65713d70f56f9538679e5a56/NP7CvcjOtLX8mST0t7eAM.png" width="300" alt="Jan-Nano-128k">
+</div>
+
+**Authors:** [Alan Dao](https://scholar.google.com/citations?user=eGWws2UAAAAJ&hl=en), [Bach Vu Dinh](https://scholar.google.com/citations?user=7Lr6hdoAAAAJ&hl=vi), [Thinh Le](https://scholar.google.com/citations?user=8tcN7xMAAAAJ&hl=en)
+
+## Overview
+
+Jan-Nano-128k represents a significant advancement in compact language models for research applications. Building upon the success of [Jan-Nano](https://huggingface.co/Menlo/Jan-nano), this enhanced version features a **native 128k context window** that enables deeper, more comprehensive research capabilities without the performance degradation typically associated with context extension methods.
+
+**Key Improvements:**
+- **🔍 Research Deeper**: Extended context allows for processing entire research papers, lengthy documents, and complex multi-turn conversations
+- **⚡ Native 128k Window**: Built from the ground up to handle long contexts efficiently, maintaining performance across the full context range  
+- **📈 Enhanced Performance**: Unlike traditional context extension methods, Jan-Nano-128k shows improved performance with longer contexts
+
+This model maintains full compatibility with Model Context Protocol (MCP) servers while dramatically expanding the scope of research tasks it can handle in a single session.
+
+## Evaluation
+
+Jan-Nano-128k has been rigorously evaluated on the SimpleQA benchmark using our MCP-based methodology, demonstrating superior performance compared to its predecessor:
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65713d70f56f9538679e5a56/Bc0ehij86l_NX52OfxeOj.png)
+
+## Why Jan-Nano-128k?
+
+Traditional approaches to extending context length, such as YaRN (Yet another RoPE extensioN), often result in performance degradation as context length increases. Jan-Nano-128k breaks this paradigm:
+
+This fundamental difference makes Jan-Nano-128k ideal for research applications requiring deep document analysis, multi-document synthesis, and complex reasoning over large information sets.
+
+## 🖥️ How to Run Locally
+
+![Jan-Nano Demo](replay.gif)
+
+Jan-Nano-128k is fully supported by [Jan - beta build](https://www.jan.ai/docs/desktop/beta), providing a seamless local AI experience with complete privacy and control.
+
+For additional tutorials and community guidance, visit our [Discussion Forums](https://huggingface.co/Menlo/Jan-nano-128k/discussions).
+
+### VLLM Deployment
+
+```bash
+vllm serve Menlo/Jan-nano-128k \
+    --host 0.0.0.0 \
+    --port 1234 \
+    --enable-auto-tool-choice \
+    --tool-call-parser hermes \
+    --rope-scaling '{"rope_type":"yarn","factor":3.2,"original_max_position_embeddings":40960}' --max-model-len 131072
+```
+
+**Note:** The chat template is included in the tokenizer. For troubleshooting, download the [Non-think chat template](https://qwen.readthedocs.io/en/latest/_downloads/c101120b5bebcc2f12ec504fc93a965e/qwen3_nonthinking.jinja).
+
+### Recommended Sampling Parameters
+
+```yaml
+Temperature: 0.7
+Top-p: 0.8
+Top-k: 20
+Min-p: 0.0
+```
+
+## 🤝 Community & Support
+
+- **Discussions**: [HuggingFace Community](https://huggingface.co/Menlo/Jan-nano-128k/discussions)
+- **Issues**: [GitHub Repository](https://github.com/menloresearch/deep-research/issues)
+- **Documentation**: [Official Docs](https://menloresearch.github.io/deep-research/)
+
+## 📄 Citation
+
+```bibtex
+@model{jan-nano-128k,
+  title={Jan-Nano-128k: Deep Research with Extended Context},
+  author={Dao, Alan and Dinh, Bach Vu and Le Thinh},
+  year={2024},
+  url={https://huggingface.co/Menlo/Jan-nano-128k}
+}
+```
+
+---
+
+*Jan-Nano-128k: Empowering deeper research through extended context understanding.*

configuration.json

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