How to use timm/vit_pe_spatial_large_patch14_448.fb with timm:
import timm model = timm.create_model("hf-hub:timm/vit_pe_spatial_large_patch14_448.fb", pretrained=True)
How to use timm/vit_pe_spatial_large_patch14_448.fb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/vit_pe_spatial_large_patch14_448.fb")
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_pe_spatial_large_patch14_448.fb", device_map="auto")
https://huggingface.co/timm/vit_pe_spatial_large_patch14_448.fb/resolve/ac6f424680a305470340dac75a0a9b4c47ee030f/README.md
hf download hf://timm/vit_pe_spatial_large_patch14_448.fb@ac6f424680a305470340dac75a0a9b4c47ee030f/README.md
curl -L -o README.md https://huggingface.co/timm/vit_pe_spatial_large_patch14_448.fb/resolve/ac6f424680a305470340dac75a0a9b4c47ee030f/README.md
tags: - image-feature-extraction - timm - transformers library_name: timm license: apache-2.0
