Text Classification
Transformers
PyTorch
Catalan
roberta
catalan
multi-class-classification
natural-language-understanding
intent-classificaiton
roberta-large
Eval Results (legacy)
text-embeddings-inference
Instructions to use projecte-aina/roberta-large-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-large-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-large-ca-v2-massive")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("projecte-aina/roberta-large-ca-v2-massive") model = AutoModelForSequenceClassification.from_pretrained("projecte-aina/roberta-large-ca-v2-massive") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f14dcf2d8745b7e04d3f40287fa78aeba46b56f403b9c7daa226f95a9ca4f5ae
- Size of remote file:
- 1.42 GB
- SHA256:
- 3a5eb5b3a905fd5085828b39dd852bd3c016b836acc3ef2c7427e4cb5f4e10be
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