Instructions to use MiniMaxAI/VTP-Base-f16d64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MiniMaxAI/VTP-Base-f16d64 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="MiniMaxAI/VTP-Base-f16d64")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MiniMaxAI/VTP-Base-f16d64", dtype="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 68312e9ce97e37f7fec4e8fca984f6b955dd0bb9fa6de7dbeed4b5d99fba699d
- Size of remote file:
- 619 kB
- SHA256:
- 99c349d6b9a075f2177fa8e0661d0157e190cdd19b4780ecc33130bb469e968b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.