Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use mnavas/roberta-finetuned-WebClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mnavas/roberta-finetuned-WebClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mnavas/roberta-finetuned-WebClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mnavas/roberta-finetuned-WebClassification") model = AutoModelForSequenceClassification.from_pretrained("mnavas/roberta-finetuned-WebClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 182dd9c4e925798cb2809d78c6481a4b15258cd3606ca2f6304c29ef6740816e
- Size of remote file:
- 1.11 GB
- SHA256:
- 6d4abab6019d8783a25ed8bf3ed71dd41173cd49052e329a179b4e17f5db03ba
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