Instructions to use fehime/clip-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fehime/clip-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="fehime/clip-model") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("fehime/clip-model") model = AutoModelForZeroShotImageClassification.from_pretrained("fehime/clip-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config_sentence_transformers.json from fehime/clip-model: direct link, hf CLI and curl.
- Browser
- Download file 118 Bytes
-
https://huggingface.co/fehime/clip-model/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://fehime/clip-model/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/fehime/clip-model/resolve/main/config_sentence_transformers.json
118 Bytes
| { | |
| "__version__": { | |
| "sentence_transformers": "2.2.0", | |
| "transformers": "4.18.0", | |
| "pytorch": "1.11.0" | |
| } | |
| } |