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Hongji Zhu
2024-04-12 16:04:57 +08:00
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README.md
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@@ -8,7 +8,7 @@
English
<p align="center">
MiniCPM-V 2.0 <a href="https://huggingface.co/openbmb/MiniCPM-V-2.0/">🤗</a> <a href="http://120.92.209.146:80/">🤖</a> |
MiniCPM-V 2.0 <a href="https://huggingface.co/openbmb/MiniCPM-V-2/">🤗</a> <a href="http://120.92.209.146:80/">🤖</a> |
OmniLMM-12B <a href="https://huggingface.co/openbmb/OmniLMM-12B/">🤗</a> <a href="http://120.92.209.146:8081">🤖</a>
</p>
@@ -501,7 +501,7 @@ pip install -r requirements.txt
### Model Zoo
| Model | Description | Download Link |
|:----------------------|:-------------------|:---------------:|
| MiniCPM-V 2.0 | The latest version for state-of-the-art end-side capabilities with high efficiency. | [🤗](https://huggingface.co/openbmb/MiniCPM-V-2.0) &nbsp;&nbsp; [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-V-2.0/files) |
| MiniCPM-V 2.0 | The latest version for state-of-the-art end-side capabilities with high efficiency. | [🤗](https://huggingface.co/openbmb/MiniCPM-V-2) &nbsp;&nbsp; [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-V-2/files) |
| MiniCPM-V | The first version of MiniCPM-V. | [🤗](https://huggingface.co/openbmb/MiniCPM-V) &nbsp;&nbsp; [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/MiniCPM-V/files) |
| OmniLMM-12B | The most capable version with leading performance. | [🤗](https://huggingface.co/openbmb/OmniLMM-12B) &nbsp;&nbsp; [<img src="./assets/modelscope_logo.png" width="20px"></img>](https://modelscope.cn/models/OpenBMB/OmniLMM-12B/files) |
@@ -518,7 +518,7 @@ import torch
from chat import OmniLMMChat, img2base64
torch.manual_seed(0)
chat_model = OmniLMMChat('openbmb/MiniCPM-V-2.0') # or 'openbmb/OmniLMM-12B'
chat_model = OmniLMMChat('openbmb/MiniCPM-V-2') # or 'openbmb/OmniLMM-12B'
im_64 = img2base64('./assets/hk_OCR.jpg')
@@ -559,10 +559,10 @@ import torch
from PIL import Image
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained('openbmb/MiniCPM-V-2.0', trust_remote_code=True, torch_dtype=torch.bfloat16)
model = AutoModel.from_pretrained('openbmb/MiniCPM-V-2', trust_remote_code=True, torch_dtype=torch.bfloat16)
model = model.to(device='mps', dtype=torch.float16)
tokenizer = AutoTokenizer.from_pretrained('openbmb/MiniCPM-V-2.0', trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained('openbmb/MiniCPM-V-2', trust_remote_code=True)
model.eval()
image = Image.open('./assets/hk_OCR.jpg').convert('RGB')