Text Classification
Transformers
PyTorch
Catalan
roberta
catalan
text classification
tecla
CaText
Catalan Textual Corpus
Eval Results (legacy)
text-embeddings-inference
Instructions to use projecte-aina/roberta-base-ca-cased-tc 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-tc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="projecte-aina/roberta-base-ca-cased-tc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("projecte-aina/roberta-base-ca-cased-tc") model = AutoModelForSequenceClassification.from_pretrained("projecte-aina/roberta-base-ca-cased-tc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from projecte-aina/roberta-base-ca-cased-tc: direct link, hf CLI and curl.
- Browser
- Download file 2.48 kB
-
https://huggingface.co/projecte-aina/roberta-base-ca-cased-tc/resolve/main/training_args.bin
- Command line
-
hf download hf://projecte-aina/roberta-base-ca-cased-tc/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/projecte-aina/roberta-base-ca-cased-tc/resolve/main/training_args.bin
2.48 kB
- Xet hash:
- e8a2813b60e3167a4a69553f9509624f084cdfa9505b612cf6368cb5a109c6a9
- Size of remote file:
- 2.48 kB
- SHA256:
- fc3ab714c61533f8f19db2d699cb8a9738339f662706bb2812ac04f87d906d7c
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