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")# 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
| { | |
| "test": { | |
| "macro_f1": 0.5694285035133362, | |
| "macro_mcc": 0.5725172758102417, | |
| "macro_precision": 0.59975266456604, | |
| "macro_recall": 0.555719792842865, | |
| "micro_f1": 0.6934136152267456, | |
| "micro_mcc": 0.692620575428009, | |
| "micro_precision": 0.690632700920105, | |
| "micro_recall": 0.6962170004844666 | |
| }, | |
| "val": { | |
| "learning_rate": 6.725102855868747e-07, | |
| "loss": 0.15798457175708394, | |
| "macro_f1": 0.5696317553520203, | |
| "macro_mcc": 0.5727673768997192, | |
| "macro_precision": 0.5995045304298401, | |
| "macro_recall": 0.5565525889396667, | |
| "micro_f1": 0.6931731104850769, | |
| "micro_mcc": 0.6923803687095642, | |
| "micro_precision": 0.6902398467063904, | |
| "micro_recall": 0.6961314082145691, | |
| "step": 99 | |
| } | |
| } |