Token Classification
Transformers
PyTorch
Catalan
roberta
catalan
named entity recognition
ner
CaText
Catalan Textual Corpus
Eval Results (legacy)
Instructions to use projecte-aina/roberta-base-ca-v2-cased-ner 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-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="projecte-aina/roberta-base-ca-v2-cased-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("projecte-aina/roberta-base-ca-v2-cased-ner") model = AutoModelForTokenClassification.from_pretrained("projecte-aina/roberta-base-ca-v2-cased-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f661936dff81ef727986b63742edf2b534e5263b3b2443b031fad11234394df1
- Size of remote file:
- 496 MB
- SHA256:
- 95be96df6bd37f3648672172bf67c39078944d8718add0e1f912ee7a7a1965ad
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