Instructions to use timm/regnety_1280.seer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/regnety_1280.seer with timm:
import timm model = timm.create_model("hf_hub:timm/regnety_1280.seer", pretrained=True) - Transformers
How to use timm/regnety_1280.seer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/regnety_1280.seer")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/regnety_1280.seer", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architecture": "regnety_1280", | |
| "num_classes": 0, | |
| "num_features": 7392, | |
| "pretrained_cfg": { | |
| "tag": "seer", | |
| "custom_load": false, | |
| "input_size": [ | |
| 3, | |
| 224, | |
| 224 | |
| ], | |
| "fixed_input_size": false, | |
| "interpolation": "bicubic", | |
| "crop_pct": 0.965, | |
| "crop_mode": "center", | |
| "mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "num_classes": 0, | |
| "pool_size": [ | |
| 7, | |
| 7 | |
| ], | |
| "first_conv": "stem.conv", | |
| "classifier": "head.fc", | |
| "license": "other", | |
| "origin_url": "https://github.com/facebookresearch/vissl" | |
| } | |
| } |