108 lines
4.5 KiB
Markdown
108 lines
4.5 KiB
Markdown
---
|
|
license: apache-2.0
|
|
language:
|
|
- en
|
|
base_model:
|
|
- Menlo/Jan-nano
|
|
pipeline_tag: text-generation
|
|
library_name: transformers
|
|
---
|
|
|
|
# Jan-Nano-128k: Empowering deeper research through extended context understanding.
|
|
<sub>*Note: Jan-Nano is a non-thinking model.*</sub>
|
|
|
|
[](https://github.com/menloresearch/deep-research)
|
|
[](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)
|
|
|
|
|
|

|
|
|
|
|
|
## 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:
|
|
|
|

|
|
|
|
## 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 desktop will eventually support this model (WIP). Otherwise you can check the deployment options below that we have tested.
|
|
|
|
For additional tutorials and community guidance, visit our [Discussion Forums](https://huggingface.co/Menlo/Jan-nano-128k/discussions).
|
|
|
|
### Deployment
|
|
|
|
Deploy using VLLM:
|
|
```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
|
|
```
|
|
|
|
Or `llama-server` from `llama.cpp`:
|
|
```bash
|
|
llama-server ... --rope-scaling yarn --rope-scale 3.2 --yarn-orig-ctx 40960
|
|
```
|
|
**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
|
|
```
|
|
|
|
## FAQ:
|
|
- I have Jinja template issue with LMStudio, how can i fix? [Here](https://huggingface.co/Menlo/Jan-nano-128k-gguf/discussions/1#6862fe2375cb85f79b28d69c)
|
|
|
|
## 🤝 Community & Support
|
|
|
|
- **Discussions**: [HuggingFace Community](https://huggingface.co/Menlo/Jan-nano-128k/discussions)
|
|
- **Issues**: [GitHub Repository](https://github.com/menloresearch/jan/issues)
|
|
- **Documentation**: [Official Docs](https://menloresearch.github.io/deep-research/)
|
|
|
|
## 📄 Citation
|
|
|
|
```bibtex
|
|
@misc{dao2025jannanotechnicalreport,
|
|
title={Jan-nano Technical Report},
|
|
author={Alan Dao and Dinh Bach Vu},
|
|
year={2025},
|
|
eprint={2506.22760},
|
|
archivePrefix={arXiv},
|
|
primaryClass={cs.CL},
|
|
url={https://arxiv.org/abs/2506.22760},
|
|
}
|
|
```
|
|
|
|
---
|
|
|
|
*Jan-Nano-128k: Empowering deeper research through extended context understanding.* |