Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use agi-css/distilroberta-base-mic-nlp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agi-css/distilroberta-base-mic-nlp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="agi-css/distilroberta-base-mic-nlp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("agi-css/distilroberta-base-mic-nlp") model = AutoModelForSequenceClassification.from_pretrained("agi-css/distilroberta-base-mic-nlp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8bd131c967b4a2f5440279b17894cabbab892e7226925f312fae9589efe0de1
- Size of remote file:
- 329 MB
- SHA256:
- 0dce83b2b14c11e834e972d2dae0dd7afea1cba21b0f613de0312133e4097fc4
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