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:
- cdc5b14ce462ebdc1610e8aa0402061b8f1994c5af9670e4d586c9a3c2abd0f0
- Size of remote file:
- 5 GB
- SHA256:
- b464cdf18a4666aa93aefd66b27e0ff785098f42a8245c1145a96dfb2cc98bae
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