Instructions to use Qdrant/clip-ViT-B-32-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Qdrant/clip-ViT-B-32-text with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Qdrant/clip-ViT-B-32-text", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Qdrant/clip-ViT-B-32-text: direct link, hf CLI and curl.
- Browser
- Download file 2.22 MB
-
https://huggingface.co/Qdrant/clip-ViT-B-32-text/resolve/main/tokenizer.json
- Command line
-
hf download hf://Qdrant/clip-ViT-B-32-text/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Qdrant/clip-ViT-B-32-text/resolve/main/tokenizer.json
2.22 MB
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