# Load model directly
from transformers import AutoProcessor, AutoModelForZeroShotImageClassification
processor = AutoProcessor.from_pretrained("rakeshjv2000/fashion-clip-vit-base-patch32")
model = AutoModelForZeroShotImageClassification.from_pretrained("rakeshjv2000/fashion-clip-vit-base-patch32", device_map="auto")Quick Links
Fashion CLIP ViT-B/32
Fine-tuned CLIP model for fashion image-text retrieval.
Model Details
- Base model: openai/clip-vit-base-patch32
- Fine-tuned on a fashion dataset
- Task: image-text similarity & retrieval
Usage
from transformers import CLIPModel, CLIPProcessor
model = CLIPModel.from_pretrained("rakeshjv2000/fashion-clip-vit-base-patch32")
processor = CLIPProcessor.from_pretrained("rakeshjv2000/fashion-clip-vit-base-patch32")
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="rakeshjv2000/fashion-clip-vit-base-patch32") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )