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@@ -30,11 +30,11 @@ We introduce two innovative techniques: Gating Logit Normalization, which enhanc
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  Skywork-MoE demonstrates comparable or superior performance to models with more parameters or more activated parameters, such as Grok-1, DBRX, Mistral 8*22, and Deepseek-V2.
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  # News and Updates
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- * 2024.6.3 We release the **Skywork-MoE-base** model.
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  # Table of contents
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- - [☁️Download URL](#Download-URL)
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  - [👨‍💻Benchmark Results](#Benchmark-Results)
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  - [🏆Demonstration of Hugging Face Model Inference](#Demonstration-of-HuggingFace-Model-Inference)
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  - [📕Demonstration of vLLM Model Inference](#Demonstration-of-vLLM-Model-Inference)
@@ -42,15 +42,8 @@ Skywork-MoE demonstrates comparable or superior performance to models with more
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  - [🤝Contact Us and Citation](#Contact-Us-and-Citation)
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- # Download URL
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-
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- | | HuggingFace Model | ModelScope Model | Wisemodel Model |
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- |:-------:|:-----------:|:-----------------------------:|:-----------------------------:|
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- | **Skywork-MoE-base** | 🤗 [Skywork-MoE-base](https://github.com/SkyworkAI/Skywork-MoE) | 🤖[Skywork-MoE-base](https://www.modelscope.cn/models/skywork/Skywork-MoE-base) | 👾[Skywork-MoE-base](https://wisemodel.cn/models/Skywork/Skywork-MoE-base) |
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- | **Skywork-MoE-Base-FP8** | 🤗 [Skywork-MoE-Base-FP8](https://github.com/SkyworkAI/Skywork-MoE) | 🤖 | 👾 |
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-
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  # Benchmark Results
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- We evaluated Skywork-MoE-base model on various popular benchmarks, including C-Eval, MMLU, CMMLU, GSM8K, MATH and HumanEval.
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  <img src="misc/skywork_moe_base_evaluation.png" alt="Image" width="600" height="280">
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  ## Quickstart with vLLM
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- We provide a method to quickly deploy the Skywork-Moe-base model based on vllm.
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- Under fp8 precision you can run Skywork-Moe-base with just only 8*4090.
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  You can get the source code in [`vllm`](https://github.com/SkyworkAI/vllm)
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@@ -128,7 +121,7 @@ docker run \
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  registry.cn-wulanchabu.aliyuncs.com/triple-mu/skywork-moe-vllm:v1
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  ```
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- Now, you can run the Skywork Moe base model for fun!
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  ### Text Completion
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  Skywork-MoE demonstrates comparable or superior performance to models with more parameters or more activated parameters, such as Grok-1, DBRX, Mistral 8*22, and Deepseek-V2.
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  # News and Updates
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+ * 2024.6.3 We release the **Skywork-MoE-Base** model.
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  # Table of contents
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+
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  - [👨‍💻Benchmark Results](#Benchmark-Results)
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  - [🏆Demonstration of Hugging Face Model Inference](#Demonstration-of-HuggingFace-Model-Inference)
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  - [📕Demonstration of vLLM Model Inference](#Demonstration-of-vLLM-Model-Inference)
 
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  - [🤝Contact Us and Citation](#Contact-Us-and-Citation)
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  # Benchmark Results
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+ We evaluated Skywork-MoE-Base model on various popular benchmarks, including C-Eval, MMLU, CMMLU, GSM8K, MATH and HumanEval.
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  <img src="misc/skywork_moe_base_evaluation.png" alt="Image" width="600" height="280">
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  ## Quickstart with vLLM
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+ We provide a method to quickly deploy the Skywork-MoE-Base model based on vllm.
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+ Under fp8 precision you can run Skywork-MoE-Base with just only 8*4090.
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  You can get the source code in [`vllm`](https://github.com/SkyworkAI/vllm)
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  registry.cn-wulanchabu.aliyuncs.com/triple-mu/skywork-moe-vllm:v1
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  ```
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+ Now, you can run the Skywork MoE model for fun!
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  ### Text Completion
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