Instructions to use linear-moe-hub/Liger-GSA-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use linear-moe-hub/Liger-GSA-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="linear-moe-hub/Liger-GSA-8B")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("linear-moe-hub/Liger-GSA-8B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use linear-moe-hub/Liger-GSA-8B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "linear-moe-hub/Liger-GSA-8B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "linear-moe-hub/Liger-GSA-8B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/linear-moe-hub/Liger-GSA-8B
- SGLang
How to use linear-moe-hub/Liger-GSA-8B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "linear-moe-hub/Liger-GSA-8B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "linear-moe-hub/Liger-GSA-8B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "linear-moe-hub/Liger-GSA-8B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "linear-moe-hub/Liger-GSA-8B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use linear-moe-hub/Liger-GSA-8B with Docker Model Runner:
docker model run hf.co/linear-moe-hub/Liger-GSA-8B
Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +39 -3
- figures/liger_framework.png +3 -0
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README.md
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---
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license: apache-2.0
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---
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license: apache-2.0
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library_name: transformers
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pipeline_tag: text-generation
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---
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# Liger-GLA-8B
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[\[📂 GitHub\]](https://github.com/OpenSparseLLMs/Linearization) [\[📜 Liger\]](https://huggingface.co/papers/2503.01496) [\[📑 arXiv\]](https://arxiv.org/abs/2503.01496)
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We introduce **Liger-GSA-8B**, a gated linear recurrent model linearized from Transformer-based LLM.
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<p align="center">
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<img width="90%" src="figures/liger_framework.png">
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</p>
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Our **Liger** framework is compatible with various linear recurrent models with gating structures:
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| Model Name | Base Model | Linear Structure | HF Link |
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| --- | --- | --- | --- |
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| Liger-GLA-8B | [Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) | [GLA](https://arxiv.org/abs/2312.06635) | [🤗 link](https://huggingface.co/linear-moe-hub/Liger-GLA-8B) |
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| Liger-GSA-8B | [Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) | [GSA](https://arxiv.org/abs/2409.07146) | [🤗 link](https://huggingface.co/linear-moe-hub/Liger-GSA-8B) |
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## Citation
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If you find this repo useful, please cite and star our work:
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```bibtex
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@article{lan2025liger,
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title={Liger: Linearizing Large Language Models to Gated Recurrent Structures},
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author={Lan, Disen and Sun, Weigao and Hu, Jiaxi and Du, Jusen and Cheng, Yu},
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journal={arXiv preprint arXiv:2503.01496},
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year={2025}
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}
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```
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figures/liger_framework.png
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Git LFS Details
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