Instructions to use keremp/opus-em-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keremp/opus-em-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="keremp/opus-em-roberta-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("keremp/opus-em-roberta-large") model = AutoModelForSequenceClassification.from_pretrained("keremp/opus-em-roberta-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7bf377b61ea136ebba007b6bd4f5c7cf0acddb21e5f39fc53dd88bfe870b71e2
- Size of remote file:
- 4.09 kB
- SHA256:
- 7eead89a9ca70b4a88a0e786ff2d8ceb4e4ffe9168b92b24e331bc2eb7ce6937
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