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
File size: 716 Bytes
786174d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | {
"architecture": "vit_giant_patch16_lingbot",
"num_classes": 0,
"num_features": 1536,
"global_pool": "avg",
"pretrained_cfg": {
"tag": "robbyant",
"custom_load": false,
"input_size": [
3,
512,
512
],
"fixed_input_size": true,
"interpolation": "bilinear",
"crop_pct": 1.0,
"crop_mode": "squash",
"mean": [
0.485,
0.456,
0.406
],
"std": [
0.229,
0.224,
0.225
],
"num_classes": 0,
"pool_size": null,
"first_conv": "patch_embed.proj",
"classifier": "head",
"license": "apache-2.0",
"origin_url": "https://github.com/robbyant/lingbot-vision",
"paper_ids": "arXiv:2607.05247"
}
} |