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")# 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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4eeb5cd917ae47dc0a84cfcfab2ea76411ddf9d8a3617a7b0aaf316c99bc6c6
- Size of remote file:
- 504 MB
- SHA256:
- 1ba4e24198351d2200806517e8888670272493dc496ef924a18611a6832e1615
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