Instructions to use EmbeddingStudio/sentence-transformers-clip-ViT-B-32-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EmbeddingStudio/sentence-transformers-clip-ViT-B-32-tokenizer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("EmbeddingStudio/sentence-transformers-clip-ViT-B-32-tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download merges.txt from EmbeddingStudio/sentence-transformers-clip-ViT-B-32-tokenizer: direct link, hf CLI and curl.
- Browser
- Download file 525 kB
-
https://huggingface.co/EmbeddingStudio/sentence-transformers-clip-ViT-B-32-tokenizer/resolve/main/merges.txt
- Command line
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hf download hf://EmbeddingStudio/sentence-transformers-clip-ViT-B-32-tokenizer/merges.txt
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curl -L -o merges.txt https://huggingface.co/EmbeddingStudio/sentence-transformers-clip-ViT-B-32-tokenizer/resolve/main/merges.txt
525 kB
File too large to display, you can check the raw version instead.