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:
- 32eeb12a877eb8de9e464ac90aecd864e1221c4570f2a6b6fb21cad90aedfb8c
- Size of remote file:
- 4.92 GB
- SHA256:
- 732013e4f5aa38814105915d5ffb75be9bcac2d094cf09a1ba43d70ecf062bf2
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