Instructions to use KETI-NLP/clip-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KETI-NLP/clip-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="KETI-NLP/clip-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("KETI-NLP/clip-roberta-base") model = AutoModel.from_pretrained("KETI-NLP/clip-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from KETI-NLP/clip-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 852 MB
-
https://huggingface.co/KETI-NLP/clip-roberta-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://KETI-NLP/clip-roberta-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/KETI-NLP/clip-roberta-base/resolve/main/pytorch_model.bin
852 MB
- Xet hash:
- f0a46e114c07824a05c3fef6d4074d7d54184aa8c70153bb2e388ab57abf53ec
- Size of remote file:
- 852 MB
- SHA256:
- 8dab599308fc85657bc6f30969ec70edec4c168343ad02b10334a248ca83b722
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