Instructions to use pbeyens/RandomCropped3-repo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pbeyens/RandomCropped3-repo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pbeyens/RandomCropped3-repo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pbeyens/RandomCropped3-repo") model = AutoModelForTokenClassification.from_pretrained("pbeyens/RandomCropped3-repo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from pbeyens/RandomCropped3-repo: direct link, hf CLI and curl.
- Browser
- Download file 521 MB
-
https://huggingface.co/pbeyens/RandomCropped3-repo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://pbeyens/RandomCropped3-repo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/pbeyens/RandomCropped3-repo/resolve/main/pytorch_model.bin
521 MB
- Xet hash:
- c665d7ce0030d16535e923163d345572e1a04fe94c8c6120a5a9b8a1044bc51b
- Size of remote file:
- 521 MB
- SHA256:
- 49e97b8c2b09af78d1c947ec1c5208203595aa0fb113067ba78a77d3a5973807
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