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@@ -409,10 +409,10 @@ Many repositories now support fine-tuning of the InternVL series models, includi
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  ### LMDeploy
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- LMDeploy is a toolkit for compressing, deploying, and serving LLM, developed by the MMRazor and MMDeploy teams.
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  ```sh
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- pip install lmdeploy>=0.5.3
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  ```
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  LMDeploy abstracts the complex inference process of multi-modal Vision-Language Models (VLM) into an easy-to-use pipeline, similar to the Large Language Model (LLM) inference pipeline.
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  LMDeploy's `api_server` enables models to be easily packed into services with a single command. The provided RESTful APIs are compatible with OpenAI's interfaces. Below are an example of service startup:
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  ```shell
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- lmdeploy serve api_server OpenGVLab/Mini-InternVL-Chat-4B-V1-5 --backend turbomind --server-port 23333
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  ```
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  To use the OpenAI-style interface, you need to install OpenAI:
 
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  ### LMDeploy
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+ LMDeploy is a toolkit for compressing, deploying, and serving LLMs & VLMs.
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  ```sh
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+ pip install lmdeploy>=0.6.4
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  ```
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  LMDeploy abstracts the complex inference process of multi-modal Vision-Language Models (VLM) into an easy-to-use pipeline, similar to the Large Language Model (LLM) inference pipeline.
 
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  LMDeploy's `api_server` enables models to be easily packed into services with a single command. The provided RESTful APIs are compatible with OpenAI's interfaces. Below are an example of service startup:
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  ```shell
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+ lmdeploy serve api_server OpenGVLab/Mini-InternVL-Chat-4B-V1-5 --server-port 23333
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  ```
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  To use the OpenAI-style interface, you need to install OpenAI: