Instructions to use edmihranyan/roberta_large_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edmihranyan/roberta_large_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="edmihranyan/roberta_large_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("edmihranyan/roberta_large_classifier") model = AutoModelForSequenceClassification.from_pretrained("edmihranyan/roberta_large_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from edmihranyan/roberta_large_classifier: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/edmihranyan/roberta_large_classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://edmihranyan/roberta_large_classifier/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/edmihranyan/roberta_large_classifier/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- b84d9fe5bb07079d7fc714d14f3f656c308631a763e43906abc7b3b037a2332e
- Size of remote file:
- 1.42 GB
- SHA256:
- db719db746389d52675549d16fd7d85bdfde87d9ddf09f6ac2ea3f9fc73e3b57
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