Instructions to use radames/blip_image_embeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radames/blip_image_embeddings with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="radames/blip_image_embeddings")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("radames/blip_image_embeddings", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b983b560099019458a5ceb75c9c0f48f8a2599262df39bf93ed44c4dcd65efb0
- Size of remote file:
- 3.69 GB
- SHA256:
- 18e10e32c7a152f087afbb72ee6ddc817ca18e10641607b9fb72e20f9b4a5f63
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