Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use JonatanGk/roberta-base-ca-finetuned-tecla with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JonatanGk/roberta-base-ca-finetuned-tecla with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JonatanGk/roberta-base-ca-finetuned-tecla")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JonatanGk/roberta-base-ca-finetuned-tecla") model = AutoModelForSequenceClassification.from_pretrained("JonatanGk/roberta-base-ca-finetuned-tecla", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c6f85a1832bdf63ddc60b8a4c6b5470598ec0167714a5bfc124f0d8925e8693
- Size of remote file:
- 504 MB
- SHA256:
- 429b4c2ec69ebfc4fdb143314f2d6c0d33715e9df9ff9eda1cf61d95d239ec9a
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