Instructions to use timm/convnextv2_tiny.fcmae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/convnextv2_tiny.fcmae with timm:
import timm model = timm.create_model("hf-hub:timm/convnextv2_tiny.fcmae", pretrained=True) - Transformers
How to use timm/convnextv2_tiny.fcmae with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/convnextv2_tiny.fcmae")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/convnextv2_tiny.fcmae", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from timm/convnextv2_tiny.fcmae: direct link, hf CLI and curl.
- Browser
- Download file 112 MB
-
https://huggingface.co/timm/convnextv2_tiny.fcmae/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://timm/convnextv2_tiny.fcmae/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/timm/convnextv2_tiny.fcmae/resolve/main/pytorch_model.bin
112 MB
- Xet hash:
- 6d0c533a5ff687968d6d9744e31b1b7b9db43a38939f09b3992a73c06e304009
- Size of remote file:
- 112 MB
- SHA256:
- d1be2e2063772045800b395295331f383801155773691d69983c324dfd6d8165
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