Instructions to use LEAF-CLIP/OpenCLIP-ViT-H-rho50-k1-constrained-FARE2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LEAF-CLIP/OpenCLIP-ViT-H-rho50-k1-constrained-FARE2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="LEAF-CLIP/OpenCLIP-ViT-H-rho50-k1-constrained-FARE2")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("LEAF-CLIP/OpenCLIP-ViT-H-rho50-k1-constrained-FARE2") model = AutoModelForZeroShotImageClassification.from_pretrained("LEAF-CLIP/OpenCLIP-ViT-H-rho50-k1-constrained-FARE2") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag and library name
#1
by nielsr HF Staff - opened
This PR improves the model card by adding the pipeline_tag and library_name.
megaelius changed pull request status to merged