Instructions to use Mooshie/eva02_large_patch14_448.dbv4-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Mooshie/eva02_large_patch14_448.dbv4-full with timm:
import timm model = timm.create_model("hf-hub:Mooshie/eva02_large_patch14_448.dbv4-full", pretrained=True) - Transformers
How to use Mooshie/eva02_large_patch14_448.dbv4-full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Mooshie/eva02_large_patch14_448.dbv4-full") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Mooshie/eva02_large_patch14_448.dbv4-full", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocess.json from Mooshie/eva02_large_patch14_448.dbv4-full: direct link, hf CLI and curl.
- Browser
- Download file 2.24 kB
-
https://huggingface.co/Mooshie/eva02_large_patch14_448.dbv4-full/resolve/main/preprocess.json
- Command line
-
hf download hf://Mooshie/eva02_large_patch14_448.dbv4-full/preprocess.json
-
curl -L -o preprocess.json https://huggingface.co/Mooshie/eva02_large_patch14_448.dbv4-full/resolve/main/preprocess.json
2.24 kB
| { | |
| "pre": [ | |
| { | |
| "background_color": "white", | |
| "interpolation": "bilinear", | |
| "size": [ | |
| 512, | |
| 512 | |
| ], | |
| "type": "pad_to_size" | |
| } | |
| ], | |
| "test": [ | |
| { | |
| "background_color": "white", | |
| "interpolation": "bilinear", | |
| "size": [ | |
| 512, | |
| 512 | |
| ], | |
| "type": "pad_to_size" | |
| }, | |
| { | |
| "antialias": true, | |
| "interpolation": "bicubic", | |
| "max_size": null, | |
| "size": [ | |
| 448, | |
| 448 | |
| ], | |
| "type": "resize" | |
| }, | |
| { | |
| "size": [ | |
| 448, | |
| 448 | |
| ], | |
| "type": "center_crop" | |
| }, | |
| { | |
| "type": "maybe_to_tensor" | |
| }, | |
| { | |
| "mean": [ | |
| 0.48145467042922974, | |
| 0.45782750844955444, | |
| 0.40821072459220886 | |
| ], | |
| "std": [ | |
| 0.2686295509338379, | |
| 0.2613025903701782, | |
| 0.27577710151672363 | |
| ], | |
| "type": "normalize" | |
| } | |
| ], | |
| "val": [ | |
| { | |
| "background_color": "white", | |
| "interpolation": "bilinear", | |
| "size": [ | |
| 512, | |
| 512 | |
| ], | |
| "type": "pad_to_size" | |
| }, | |
| { | |
| "antialias": true, | |
| "interpolation": "bicubic", | |
| "max_size": null, | |
| "size": [ | |
| 448, | |
| 448 | |
| ], | |
| "type": "resize" | |
| }, | |
| { | |
| "size": [ | |
| 448, | |
| 448 | |
| ], | |
| "type": "center_crop" | |
| }, | |
| { | |
| "type": "maybe_to_tensor" | |
| }, | |
| { | |
| "mean": [ | |
| 0.48145467042922974, | |
| 0.45782750844955444, | |
| 0.40821072459220886 | |
| ], | |
| "std": [ | |
| 0.2686295509338379, | |
| 0.2613025903701782, | |
| 0.27577710151672363 | |
| ], | |
| "type": "normalize" | |
| } | |
| ] | |
| } |