Instructions to use cringgaard/sail-clip-hendrix-10epochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cringgaard/sail-clip-hendrix-10epochs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="cringgaard/sail-clip-hendrix-10epochs") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("cringgaard/sail-clip-hendrix-10epochs") model = AutoModelForZeroShotImageClassification.from_pretrained("cringgaard/sail-clip-hendrix-10epochs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ec81c69a96e5ae01110ef711ca2a566ab54e4a60d7a57790a4dbf471cddda14
- Size of remote file:
- 5.3 kB
- SHA256:
- 4c4c3a6f92ec33a96e3852ba31b15fb23b4c7f1110da210efe8720b5778646a4
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