Instructions to use timm/convnextv2_atto.fcmae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/convnextv2_atto.fcmae with timm:
import timm model = timm.create_model("hf_hub:timm/convnextv2_atto.fcmae", pretrained=True) - Transformers
How to use timm/convnextv2_atto.fcmae with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/convnextv2_atto.fcmae")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/convnextv2_atto.fcmae", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4905ded7bb3e37f864578bb2e8e1005032c5cdf4bf398e8a7614973e15f42c81
- Size of remote file:
- 13.6 MB
- SHA256:
- 4c79d70e9b6f564580be781da4d9d3790fa7c471da5c53299bfd12d5832115d2
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