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-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-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-cased-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("projecte-aina/roberta-base-ca-cased-ner") model = AutoModelForTokenClassification.from_pretrained("projecte-aina/roberta-base-ca-cased-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from projecte-aina/roberta-base-ca-cased-ner: direct link, hf CLI and curl.
- Browser
- Download file 502 MB
-
https://huggingface.co/projecte-aina/roberta-base-ca-cased-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://projecte-aina/roberta-base-ca-cased-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/projecte-aina/roberta-base-ca-cased-ner/resolve/main/pytorch_model.bin
502 MB
- Xet hash:
- 29ca4915c238fa4dffa8561d189817d1e02e7c6320234b0afcb4c248511f0782
- Size of remote file:
- 502 MB
- SHA256:
- 719187b33d8de05d7e4f9e21846b378b9b9e1f1b4716ac29e9874d895a57cfc3
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