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:
- a7016691a46f18682eb7e9e421ddd3c0f658a23505f94e73c55b69d9823f504d
- Size of remote file:
- 3.06 kB
- SHA256:
- 700cd44a451588be92991f34c247e3dad7fc762c81c75ae9d32cc4eaa7242bb3
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