Text Classification
Transformers
PyTorch
Catalan
roberta
catalan
textual entailment
teca
CaText
Catalan Textual Corpus
Eval Results (legacy)
text-embeddings-inference
Instructions to use projecte-aina/roberta-base-ca-v2-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-v2-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-v2-cased-te")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("projecte-aina/roberta-base-ca-v2-cased-te") model = AutoModelForSequenceClassification.from_pretrained("projecte-aina/roberta-base-ca-v2-cased-te") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbfdba66c5ebb32e0f6bab57acdc0d225c15f064a8f7291659cfdaa5a58dfb01
- Size of remote file:
- 499 MB
- SHA256:
- a06de16611b37b1379645a1849a9996dc983a11b72efd67fd4027245c24a9de7
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