Instructions to use orzhan/ruroberta-ruatd-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use orzhan/ruroberta-ruatd-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="orzhan/ruroberta-ruatd-binary")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("orzhan/ruroberta-ruatd-binary") model = AutoModelForSequenceClassification.from_pretrained("orzhan/ruroberta-ruatd-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from orzhan/ruroberta-ruatd-binary: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/orzhan/ruroberta-ruatd-binary/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://orzhan/ruroberta-ruatd-binary/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/orzhan/ruroberta-ruatd-binary/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- b02f7855aa9df98afae5795b0245b7daaf00ef3b86efec567489e16077ebf5a2
- Size of remote file:
- 1.42 GB
- SHA256:
- 7a6d25413de20dd4891888b94136d9c1d52a305bf8fc7003561835ea11c98644
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