Instructions to use MiniMaxAI/VTP-Large-f16d64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MiniMaxAI/VTP-Large-f16d64 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="MiniMaxAI/VTP-Large-f16d64")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MiniMaxAI/VTP-Large-f16d64", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50b0823451cb8ad6fa99576642db511dd7e85c96ff7f5f7629c8c4b8f47acefa
- Size of remote file:
- 2.93 GB
- SHA256:
- de5df2006083a9536c4d3ea36c6ae2181ec604e06550f1b2d7cece3b16aac32f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.