Instructions to use belfner/vit_small_patch16_lingbot.robbyant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use belfner/vit_small_patch16_lingbot.robbyant with timm:
import timm model = timm.create_model("hf_hub:belfner/vit_small_patch16_lingbot.robbyant", pretrained=True) - Transformers
How to use belfner/vit_small_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_small_patch16_lingbot.robbyant")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("belfner/vit_small_patch16_lingbot.robbyant", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "variant": "small", | |
| "arch": "vit_small_patch16_lingbot", | |
| "tag": "robbyant", | |
| "source_repo": "robbyant/lingbot-vision-vit-small", | |
| "source_revision": "127cbcec380de0bcd55bdc1b1fad3819850a6514", | |
| "source_sha256": "dca36562cb6b0b34504df6edc18fa282c5ef06fb375c3e91d5487247a1096f9d", | |
| "wrapper_key": "model", | |
| "source_tensors": 188, | |
| "converted_tensors": 186, | |
| "param_count": 21596160, | |
| "dtypes": [ | |
| "torch.float32" | |
| ], | |
| "save_dir": "/home/belfner/PycharmProjects/pytorch-image-models/converted/vit_small_patch16_lingbot.robbyant", | |
| "artifacts": { | |
| "config.json": "2262dd5a2bd838c83671a33638894af6711712f1f04b6c8ba1a39df8779e5a04", | |
| "model.safetensors": "f879b5b2352b0925d9ec12bdbfdbfeea4973ea0190f3a80232a9a451bbf895ee", | |
| "pytorch_model.bin": "1ee09c96c84d9d7fb3332f41984da1b0083f78438652ce1ba02179074082d4cf", | |
| "README.md": "11ee10680d95dda5f1368bc9f1b68cee14c448cb7af908dbf67fdf65fe620f06" | |
| }, | |
| "parity": { | |
| "512x512": { | |
| "cls": { | |
| "max_abs": 0.0, | |
| "mean_abs": 0.0, | |
| "cos_min": 1.0 | |
| }, | |
| "registers": { | |
| "max_abs": 0.0, | |
| "mean_abs": 0.0, | |
| "cos_min": 1.0 | |
| }, | |
| "patches": { | |
| "max_abs": 0.0, | |
| "mean_abs": 0.0, | |
| "cos_min": 0.9999997615814209 | |
| } | |
| }, | |
| "384x512": { | |
| "cls": { | |
| "max_abs": 0.0, | |
| "mean_abs": 0.0, | |
| "cos_min": 1.0000001192092896 | |
| }, | |
| "registers": { | |
| "max_abs": 0.0, | |
| "mean_abs": 0.0, | |
| "cos_min": 0.9999999403953552 | |
| }, | |
| "patches": { | |
| "max_abs": 0.0, | |
| "mean_abs": 0.0, | |
| "cos_min": 0.9999997615814209 | |
| } | |
| }, | |
| "public_forward_token_pool": { | |
| "max_abs": 0.0 | |
| }, | |
| "public_forward_avg_pool_smoke": "pass", | |
| "transform_max_abs": 0.0, | |
| "real_image": { | |
| "cls": { | |
| "max_abs": 0.0, | |
| "mean_abs": 0.0, | |
| "cos_min": 1.0 | |
| }, | |
| "registers": { | |
| "max_abs": 0.0, | |
| "mean_abs": 0.0, | |
| "cos_min": 0.9999999403953552 | |
| }, | |
| "patches": { | |
| "max_abs": 0.0, | |
| "mean_abs": 0.0, | |
| "cos_min": 0.9999997019767761 | |
| } | |
| } | |
| }, | |
| "provenance": { | |
| "converter_sha256": "166732a819c7af4542c50477c5ceeb01f3dc20061fef300f6a4fc437df48640c", | |
| "timm_root": "/home/belfner/PycharmProjects/pytorch-image-models", | |
| "timm_commit": "1fb842c917df1edd3c4a7c17edc4fc5588452cc5", | |
| "timm_dirty": false, | |
| "reference_root": "/home/belfner/PycharmProjects/pytorch-image-models/lingbot-vision", | |
| "reference_commit": "151e46321bae4399f8568829f190c7bdec216b49", | |
| "reference_dirty": false, | |
| "torch": "2.13.0+cu130", | |
| "timm_version": "1.0.29.dev0", | |
| "safetensors": "0.8.0", | |
| "huggingface_hub": "1.25.1", | |
| "python": "3.14.0" | |
| } | |
| } |