Token Classification
Transformers
PyTorch
Catalan
roberta
catalan
part of speech tagging
pos
CaText
Catalan Textual Corpus
Eval Results (legacy)
Instructions to use projecte-aina/roberta-base-ca-cased-pos 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-pos 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-pos")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("projecte-aina/roberta-base-ca-cased-pos") model = AutoModelForTokenClassification.from_pretrained("projecte-aina/roberta-base-ca-cased-pos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from projecte-aina/roberta-base-ca-cased-pos: direct link, hf CLI and curl.
- Browser
- Download file 502 MB
-
https://huggingface.co/projecte-aina/roberta-base-ca-cased-pos/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://projecte-aina/roberta-base-ca-cased-pos/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/projecte-aina/roberta-base-ca-cased-pos/resolve/main/pytorch_model.bin
502 MB
- Xet hash:
- 243eadcc872b12ea0cff380ea58220442b0e185767509f548e12ec8807da8612
- Size of remote file:
- 502 MB
- SHA256:
- 4a3ef85b9bd9c626ef882eabb3f68e19f65d88416f8187ca0fed5e17724f34a4
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