Instructions to use natihash/vit_base_patch16_clip_224.text_fft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use natihash/vit_base_patch16_clip_224.text_fft with timm:
import timm model = timm.create_model("hf_hub:natihash/vit_base_patch16_clip_224.text_fft", pretrained=True) - Transformers
How to use natihash/vit_base_patch16_clip_224.text_fft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="natihash/vit_base_patch16_clip_224.text_fft") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("natihash/vit_base_patch16_clip_224.text_fft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - image-classification | |
| - timm | |
| - transformers | |
| pipeline_tag: image-classification | |
| library_name: timm | |
| license: apache-2.0 | |
| # Model card for vit_base_patch16_clip_224.text_fft | |