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 optimizer.pt from edmihranyan/roberta_large_classifier: direct link, hf CLI and curl.
- Browser
- Download file 2.84 GB
-
https://huggingface.co/edmihranyan/roberta_large_classifier/resolve/main/optimizer.pt
- Command line
-
hf download hf://edmihranyan/roberta_large_classifier/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/edmihranyan/roberta_large_classifier/resolve/main/optimizer.pt
2.84 GB
- Xet hash:
- 60065e6d1b3f794cdf8889e40eab59ffec062d99560f77c8bb67e149b18bc9d4
- Size of remote file:
- 2.84 GB
- SHA256:
- 9df5b1c2b78a5ebd825ca48d31bbbcf42990e7908768043e5f56c5e04b5c6dbb
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