commit c31311c375327168b13384d29d966e248cfeb3ec Author: ModelHub XC Date: Sun Aug 30 01:32:16 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: gabriellarson/Lucy-128k-GGUF Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..cc3e493 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,61 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx 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+ Lucy-128k +
+ +**Authors:** [Alan Dao](https://scholar.google.com/citations?user=eGWws2UAAAAJ&hl=en), [Bach Vu Dinh](https://scholar.google.com/citations?user=7Lr6hdoAAAAJ&hl=vi), [Alex Nguyen](https://github.com/nguyenhoangthuan99) + + +![image/gif](lucy_demo.gif) + + +## Overview + +Lucy is a compact but capable 1.7B model focused on agentic web search and lightweight browsing. Built on [Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B), Lucy inherits deep research capabilities from larger models while being optimized to run efficiently on mobile devices, even with CPU-only configurations. + +We achieved this through machine-generated task vectors that optimize thinking processes, smooth reward functions across multiple categories, and pure reinforcement learning without any supervised fine-tuning. + +## What Lucy Excels At + +- **🔍 Strong Agentic Search**: Powered by MCP-enabled tools (e.g., Serper with Google Search) +- **🌐 Basic Browsing Capabilities**: Through Crawl4AI (MCP server to be released), Serper,... +- **📱 Mobile-Optimized**: Lightweight enough to run on CPU or mobile devices with decent speed +- **🎯 Focused Reasoning**: Machine-generated task vectors optimize thinking processes for search tasks + +## Evaluation +Following the same MCP benchmark methodology used for [Jan-Nano](https://huggingface.co/Menlo/Jan-nano) and [Jan-Nano-128k](https://huggingface.co/Menlo/Jan-nano-128k), Lucy demonstrates impressive performance despite being only a 1.7B model, achieving higher accuracy than DeepSeek-v3 on [SimpleQA](https://openai.com/index/introducing-simpleqa/). + +![image/png](https://cdn-uploads.huggingface.co/production/uploads/65713d70f56f9538679e5a56/lG2FqLCWXq1N8lh7wlJgW.png) + +## 🖥️ How to Run Locally + +Lucy can be deployed using various methods including vLLM, llama.cpp, or through local applications like Jan, LMStudio, and other compatible inference engines. The model supports integration with search APIs and web browsing tools through the MCP. + +### Deployment + +Deploy using VLLM: +```bash +vllm serve Menlo/Lucy-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 +``` + +### Recommended Sampling Parameters + +```yaml +Temperature: 0.7 +Top-p: 0.9 +Top-k: 20 +Min-p: 0.0 +``` + +## 🤝 Community & Support + +- **Discussions**: [HuggingFace Community](https://huggingface.co/Menlo/Lucy-128k/discussions) + +## 📄 Citation + +**Paper (coming soon)**: *Lucy: edgerunning agentic web search on mobile with machine generated task vectors.* \ No newline at end of file