Instructions to use Gflorent/clip-text-feature-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gflorent/clip-text-feature-extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Gflorent/clip-text-feature-extraction")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Gflorent/clip-text-feature-extraction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3dee9f77912766e18c16b8950697b802db9eb757e4acff0d63a8ec35550b81a3
- Size of remote file:
- 605 MB
- SHA256:
- e4bd48fae7b40d1affb32af3b665a6ff7f4868eee35014b9d94cbdee184fb047
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