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:
- 96728d6e8571b4de00ebbbf23aa188ee2b4065ff5e7fd6dfb6186e521078870a
- Size of remote file:
- 4.98 GB
- SHA256:
- 289119f6ba78e12707d5a41ddf5a360f3a75c6c153184a15b1759fc07901480b
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