Feature Extraction
Transformers
Safetensors
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bamboo
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@@ -16,7 +16,7 @@ This insight opens up new avenues for inference speed, akin to MoE's selective a
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  By dynamically choosing model parameters for computation, we can substantially boost inference speed.
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  However, the widespread adoption of ReLU-based models in the LLM field remains limited.
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- Here we introduce a new 7B ReLU-based LLM, Bamboo (Github link:[https://github.com/SJTU-IPADS/Bamboo](https://github.com/SJTU-IPADS/Bamboo)),
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  which boasts nearly 85% sparsity and performance levels on par with [Mistral-7B](https://huggingface.co/mistralai/Mistral-7B-v0.1).
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  ## Model Architecture
 
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  By dynamically choosing model parameters for computation, we can substantially boost inference speed.
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  However, the widespread adoption of ReLU-based models in the LLM field remains limited.
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+ Here we introduce a new 7B ReLU-based LLM, Bamboo (Github link: [https://github.com/SJTU-IPADS/Bamboo](https://github.com/SJTU-IPADS/Bamboo)),
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  which boasts nearly 85% sparsity and performance levels on par with [Mistral-7B](https://huggingface.co/mistralai/Mistral-7B-v0.1).
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  ## Model Architecture