Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use agi-css/distilroberta-base-etc-nlp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agi-css/distilroberta-base-etc-nlp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="agi-css/distilroberta-base-etc-nlp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("agi-css/distilroberta-base-etc-nlp") model = AutoModelForSequenceClassification.from_pretrained("agi-css/distilroberta-base-etc-nlp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc5e3ae000a8618c70e4c38d0b97e3b2fe082532c82c6858f72e7b1732ae9799
- Size of remote file:
- 329 MB
- SHA256:
- d2c2ca4ea0d6584331cccf59f89289c765f30a98a5d70d46a515b7a7936c8101
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