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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54c94ce37d65fc715463a1f6f44c95d7c820ecd4ecc96c5ea58a6963937eb524
- Size of remote file:
- 3.12 kB
- SHA256:
- 67349590f5aec879a63aa0b062060502bb16ac8f745371384a5684744bfb8c85
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