Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use agi-css/distilroberta-base-mic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agi-css/distilroberta-base-mic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="agi-css/distilroberta-base-mic")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("agi-css/distilroberta-base-mic") model = AutoModelForSequenceClassification.from_pretrained("agi-css/distilroberta-base-mic") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49716dbe10e3605d46a657761c67c4976c54110561b8c9f5fd5242e8ad4fe96b
- Size of remote file:
- 329 MB
- SHA256:
- f4a5c6cd5c05a35855dec7faaad6d802459d41ebced2d37c5665d5371aa93f3d
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