Instructions to use LinaAlhuri/clip-vit-large-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LinaAlhuri/clip-vit-large-patch32 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import HybridCLIP model = HybridCLIP.from_pretrained("LinaAlhuri/clip-vit-large-patch32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from LinaAlhuri/clip-vit-large-patch32: direct link, hf CLI and curl.
- Browser
- Download file 2.58 GB
-
https://huggingface.co/LinaAlhuri/clip-vit-large-patch32/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://LinaAlhuri/clip-vit-large-patch32/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/LinaAlhuri/clip-vit-large-patch32/resolve/main/flax_model.msgpack
2.58 GB
- Xet hash:
- 2330599f2463919dc92235b320af602d010fe0f59eee59b40e622167ee2913af
- Size of remote file:
- 2.58 GB
- SHA256:
- 55cc56b2dcc217b7943d277d878befca3090329f2e2c850c00f5290a1545fdad
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