Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
clip
feature-extraction
custom_code
# Load model directly
from transformers import AutoProcessor, AutoModel
processor = AutoProcessor.from_pretrained("chuhac/BiomedCLIP-vit-bert-hf", trust_remote_code=True)
model = AutoModel.from_pretrained("chuhac/BiomedCLIP-vit-bert-hf", trust_remote_code=True, device_map="auto")Quick Links
Huggingface-friendly BiomedCLIP
- pure torch and huggingface-based implementation of the original microsoft/BiomedCLIP-PubMedBERT_256-vit_base_patch16_224
- rename the checkpoint state key names.
Usage
from transformers import AutoModel, AutoProcessor
model = AutoModel.from_pretrained("chuhac/BiomedCLIP-vit-bert-hf", trust_remote_code=True)
processor = AutoProcessor.from_pretrained("chuhac/BiomedCLIP-vit-bert-hf", trust_remote_code=True)
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="chuhac/BiomedCLIP-vit-bert-hf", trust_remote_code=True)