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:
- c2d838642448588d92365f81f19d40807b00ff55701275a52399771c5f59255c
- Size of remote file:
- 1.42 GB
- SHA256:
- 74f7422b08538b2171fd1e54bb061c9b5e0ef1e2622321852c5468c43c2181f1
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