Video-Text-to-Text
Transformers
Safetensors
minicpmv
feature-extraction
MiniCPM-V
finetune
MLLM
custom_code
Instructions to use xjtupanda/MiniCPM-V-200K-video-finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xjtupanda/MiniCPM-V-200K-video-finetune with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("xjtupanda/MiniCPM-V-200K-video-finetune", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f23ee38ca719a20c430529b82f6ea8ce7566b52f97db2597b0f1cd032c65fdc7
- Size of remote file:
- 2.18 GB
- SHA256:
- 546697f585489e3c844fc5246fe07b47d0154e7a57d86f5c44a1d7aa8fb92ad7
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