Instructions to use timm/convnextv2_femto.fcmae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/convnextv2_femto.fcmae with timm:
import timm model = timm.create_model("hf_hub:timm/convnextv2_femto.fcmae", pretrained=True) - Transformers
How to use timm/convnextv2_femto.fcmae with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/convnextv2_femto.fcmae")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/convnextv2_femto.fcmae", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7e48fcdf0470dd0ef749a8ffc3473ebdd1159c680e58226fd63e83ee8917b1a
- Size of remote file:
- 19.4 MB
- SHA256:
- 9ccf049f2f48124e55a5d062975ecd6e23258274cb05900a1cda450ab9ff561c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.