59 lines
1.8 KiB
Markdown
59 lines
1.8 KiB
Markdown
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---
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library_name: transformers
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license: other
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license_name: lfm1.0
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license_link: LICENSE
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language:
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- en
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- ar
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- zh
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- fr
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- de
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- ja
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- ko
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- es
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pipeline_tag: text-generation
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tags:
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- liquid
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- lfm2
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- edge
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- moe
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- llama.cpp
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- gguf
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base_model:
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- LiquidAI/LFM2-8B-A1B
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---
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<center>
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<div style="text-align: center;">
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<img
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src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png"
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alt="Liquid AI"
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style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;"
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/>
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</div>
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<div style="display: flex; justify-content: center; gap: 0.5em;">
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<a href="https://playground.liquid.ai/chat">
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<a href="https://playground.liquid.ai/"><strong>Try LFM</strong></a> • <a href="https://docs.liquid.ai/lfm"><strong>Documentation</strong></a> • <a href="https://leap.liquid.ai/"><strong>LEAP</strong></a></a>
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</div>
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</center>
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# LFM2-8B-A1B-GGUF
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LFM2 is a new generation of hybrid models developed by [Liquid AI](https://www.liquid.ai/), specifically designed for edge AI and on-device deployment. It sets a new standard in terms of quality, speed, and memory efficiency.
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We're releasing the weights of our first MoE based on LFM2, with 8.3B total parameters and 1.5B active parameters.
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- LFM2-8B-A1B is the best on-device MoE in terms of both **quality** (comparable to 3-4B dense models) and **speed** (faster than Qwen3-1.7B).
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- **Code and knowledge** capabilities are significantly improved compared to LFM2-2.6B.
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- Quantized variants fit comfortably on high-end **phones, tablets, and laptops**.
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Find more information about LFM2-8B-A1B in our [blog post](https://www.liquid.ai/blog/).
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## 🏃 How to run LFM2
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Example usage with [llama.cpp](https://github.com/ggml-org/llama.cpp):
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```
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llama-cli -hf LiquidAI/LFM2-8B-A1B-GGUF
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```
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