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update readme
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@@ -477,10 +477,11 @@ pip install -r requirements.txt
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### Model Zoo
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### Model Zoo
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| Model | GPU Memory |          Description | Download Link |
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| Model | Memory |          Description | Download |
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|:-----------|:-----------:|:-------------------|:---------------:|
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|:-----------|:-----------:|:-------------------|:---------------:|
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| MiniCPM-Llama3-V 2.5 | 19 GB | The lastest version, achieving state-of-the end-side multimodal performance. | [🤗](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5/) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-Llama3-V-2_5) |
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| MiniCPM-Llama3-V 2.5 | 19 GB | The lastest version, achieving state-of-the end-side multimodal performance. | [🤗](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5/) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-Llama3-V-2_5) |
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| MiniCPM-Llama3-V 2.5 int4 | 8 GB | int4 quantized version,lower GPU memory usage. | [🤗](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5-int4/) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-Llama3-V-2_5-int4) |
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| MiniCPM-Llama3-V 2.5 gguf | 5 GB | The gguf version, lower GPU memory and faster inference. | [🤗](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5-gguf) |
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| MiniCPM-Llama3-V 2.5 int4 | 8 GB | The int4 quantized version,lower GPU memory usage. | [🤗](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5-int4/) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-Llama3-V-2_5-int4) |
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| MiniCPM-V 2.0 | 8 GB | Light version, balance the performance the computation cost. | [🤗](https://huggingface.co/openbmb/MiniCPM-V-2) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-V-2) |
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| MiniCPM-V 2.0 | 8 GB | Light version, balance the performance the computation cost. | [🤗](https://huggingface.co/openbmb/MiniCPM-V-2) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-V-2) |
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| MiniCPM-V 1.0 | 7 GB | Lightest version, achieving the fastest inference. | [🤗](https://huggingface.co/openbmb/MiniCPM-V) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-V) |
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| MiniCPM-V 1.0 | 7 GB | Lightest version, achieving the fastest inference. | [🤗](https://huggingface.co/openbmb/MiniCPM-V) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-V) |
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@@ -491,6 +491,7 @@ pip install -r requirements.txt
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| 模型 | 显存占用 |          简介 | 下载链接 |
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| 模型 | 显存占用 |          简介 | 下载链接 |
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|:--------------|:--------:|:-------------------|:---------------:|
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|:--------------|:--------:|:-------------------|:---------------:|
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| MiniCPM-Llama3-V 2.5| 19 GB | 最新版本,提供最佳的端侧多模态理解能力。 | [🤗](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5/) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-Llama3-V-2_5) |
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| MiniCPM-Llama3-V 2.5| 19 GB | 最新版本,提供最佳的端侧多模态理解能力。 | [🤗](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5/) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-Llama3-V-2_5) |
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| MiniCPM-Llama3-V 2.5 gguf | 5 GB | gguf 版本,更低的内存占用和更高的推理效率。 | [🤗](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5-gguf) |
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| MiniCPM-Llama3-V 2.5 int4 | 8 GB | int4量化版,更低显存占用。 | [🤗](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5-int4/) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-Llama3-V-2_5-int4) |
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| MiniCPM-Llama3-V 2.5 int4 | 8 GB | int4量化版,更低显存占用。 | [🤗](https://huggingface.co/openbmb/MiniCPM-Llama3-V-2_5-int4/) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-Llama3-V-2_5-int4) |
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| MiniCPM-V 2.0 | 8 GB | 轻量级版本,平衡计算开销和多模态理解能力。 | [🤗](https://huggingface.co/openbmb/MiniCPM-V-2) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-V-2) |
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| MiniCPM-V 2.0 | 8 GB | 轻量级版本,平衡计算开销和多模态理解能力。 | [🤗](https://huggingface.co/openbmb/MiniCPM-V-2) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-V-2) |
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| MiniCPM-V 1.0 | 7 GB | 最轻量版本, 提供最快的推理速度。 | [🤗](https://huggingface.co/openbmb/MiniCPM-V) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-V) |
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| MiniCPM-V 1.0 | 7 GB | 最轻量版本, 提供最快的推理速度。 | [🤗](https://huggingface.co/openbmb/MiniCPM-V) [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-V) |
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