Instructions to use timm/regnetx_016.pycls_in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/regnetx_016.pycls_in1k with timm:
import timm model = timm.create_model("hf_hub:timm/regnetx_016.pycls_in1k", pretrained=True) - Transformers
How to use timm/regnetx_016.pycls_in1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="timm/regnetx_016.pycls_in1k") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/regnetx_016.pycls_in1k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from timm/regnetx_016.pycls_in1k: direct link, hf CLI and curl.
- Browser
- Download file 37.1 MB
-
https://huggingface.co/timm/regnetx_016.pycls_in1k/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://timm/regnetx_016.pycls_in1k/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/timm/regnetx_016.pycls_in1k/resolve/main/pytorch_model.bin
37.1 MB
- Xet hash:
- 98bb655fb403bb9288c098772f29d7eb7ca79fdf1bb61ad940dbd6a1caa59d14
- Size of remote file:
- 37.1 MB
- SHA256:
- 2766629d6cd56dea96e36d372cbfcdf8291851bb472a22e6ecba5af47817e76d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.