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
| {"bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "eos_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "unk_token": {"content": "<unk>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "sep_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "pad_token": {"content": "<pad>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "cls_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true}} |