Instructions to use BilelDJ/clip-hugging-face-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BilelDJ/clip-hugging-face-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="BilelDJ/clip-hugging-face-finetuned") 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("BilelDJ/clip-hugging-face-finetuned") model = AutoModelForZeroShotImageClassification.from_pretrained("BilelDJ/clip-hugging-face-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 2.0, | |
| "total_flos": 5816699796600.0, | |
| "train_loss": 1.3652541448495217, | |
| "train_runtime": 216.8469, | |
| "train_samples_per_second": 0.461, | |
| "train_steps_per_second": 0.065 | |
| } |