Instructions to use belfner/vit_giant_patch16_lingbot.robbyant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use belfner/vit_giant_patch16_lingbot.robbyant with timm:
import timm model = timm.create_model("hf_hub:belfner/vit_giant_patch16_lingbot.robbyant", pretrained=True) - Transformers
How to use belfner/vit_giant_patch16_lingbot.robbyant with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="belfner/vit_giant_patch16_lingbot.robbyant")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("belfner/vit_giant_patch16_lingbot.robbyant", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35b33de3c6b315c7421b0f9e32a5dfcd1d3bffc82f15b392598a7aeeaa5a92fe
- Size of remote file:
- 4.54 GB
- SHA256:
- b97d9e03afbc2217d89fd91505e66ea57c9d172060765165d483327adb1e1efe
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