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-v2-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-v2-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-v2-cased-tc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("projecte-aina/roberta-base-ca-v2-cased-tc") model = AutoModelForSequenceClassification.from_pretrained("projecte-aina/roberta-base-ca-v2-cased-tc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a95125e9c8ba50cb1229602472f26b1cd5f6d260fb5373ae7176e02ec8039e5c
- Size of remote file:
- 499 MB
- SHA256:
- c4e13e309d6f6b36be7736992f9164db10e421c8abadf61128f44759237fd686
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