Instructions to use timm/vit_pe_lang_large_patch14_448.fb_tiling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_pe_lang_large_patch14_448.fb_tiling with timm:
import timm model = timm.create_model("hf_hub:timm/vit_pe_lang_large_patch14_448.fb_tiling", pretrained=True) - Transformers
How to use timm/vit_pe_lang_large_patch14_448.fb_tiling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/vit_pe_lang_large_patch14_448.fb_tiling")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_pe_lang_large_patch14_448.fb_tiling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
b8571a6 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:0a24e3625d8c4aa1dd434b30d5248decdc77197155a3ac660aca078a989252bd
size 1165779046
|