Text Classification
Transformers
PyTorch
Catalan
roberta
catalan
teca
CaText
Catalan Textual Corpus
Eval Results (legacy)
text-embeddings-inference
Instructions to use projecte-aina/roberta-base-ca-cased-te with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use projecte-aina/roberta-base-ca-cased-te with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="projecte-aina/roberta-base-ca-cased-te")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("projecte-aina/roberta-base-ca-cased-te") model = AutoModelForSequenceClassification.from_pretrained("projecte-aina/roberta-base-ca-cased-te") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a2f0c8bc15fb99fb838e0f7e57f1b890249c9ce87d7c99b36bc23f6050d2859
- Size of remote file:
- 49.1 MB
- SHA256:
- 767fab7545b0cbbfae578348bab15195548649b2efccfd04a94d1b1bdabf1723
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