Text Classification
Transformers
PyTorch
Catalan
roberta
catalan
multi-class-classification
natural-language-understanding
intent-classificaiton
Eval Results (legacy)
text-embeddings-inference
Instructions to use projecte-aina/roberta-base-ca-v2-massive 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-massive 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-massive")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("projecte-aina/roberta-base-ca-v2-massive") model = AutoModelForSequenceClassification.from_pretrained("projecte-aina/roberta-base-ca-v2-massive", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae4186ff7de1649335f944d93db2d95055429b4fb4ef14ceb3b023e5893abc16
- Size of remote file:
- 499 MB
- SHA256:
- 9ec43031f42cea9c3c1da981f785d2508fcaf8386f022a314fa966fe5796cb62
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