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https://github.com/OpenBMB/MiniCPM-V.git
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update readme
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14
README_en.md
14
README_en.md
@@ -279,7 +279,7 @@ MiniCPM-V 2.6 can be easily used in various ways: (1) [llama.cpp](https://github
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<td>34B</td>
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<td>157</td>
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<td>-</td>
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<td>2141</td>
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<td>2141.0</td>
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<td>59.3</td>
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<td>518</td>
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<td>48.0</td>
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@@ -830,11 +830,18 @@ We deploy MiniCPM-V 2.6 on end devices. The demo video is the raw screen recordi
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</p>
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</table>
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<table align="center">
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<p align="center">
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<img src="assets/gif_cases/ticket.gif" width=32%/>
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<img src="assets/gif_cases/wfh.gif" width=32%/>
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</p>
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</table>
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<table align="center">
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<p align="center">
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<video src="https://github.com/user-attachments/assets/21f4b818-ede1-4822-920e-91281725c830" width="360" /> </video>
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<video src="https://github.com/user-attachments/assets/c835f757-206b-4d9c-8e36-70d67b453628" width="360" /> </video>
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<!-- <video src="https://github.com/user-attachments/assets/c835f757-206b-4d9c-8e36-70d67b453628" width="360" /> </video> -->
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</p>
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</table>
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@@ -1416,7 +1423,7 @@ model = AutoModel.from_pretrained('openbmb/MiniCPM-V-2_6', trust_remote_code=Tru
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model = model.eval().cuda()
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tokenizer = AutoTokenizer.from_pretrained('openbmb/MiniCPM-V-2_6', trust_remote_code=True)
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MAX_NUM_FRAMES=64
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MAX_NUM_FRAMES=64 # if cuda OOM set a smaller number
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def encode_video(video_path):
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def uniform_sample(l, n):
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@@ -1442,6 +1449,7 @@ msgs = [
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]
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# Set decode params for video
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params = {}
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params["use_image_id"] = False
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params["max_slice_nums"] = 2 # use 1 if cuda OOM and video resolution > 448*448
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