Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use agi-css/distilroberta-base-mic-sym with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agi-css/distilroberta-base-mic-sym with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="agi-css/distilroberta-base-mic-sym")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("agi-css/distilroberta-base-mic-sym") model = AutoModelForSequenceClassification.from_pretrained("agi-css/distilroberta-base-mic-sym") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b36ca9713acbe8bebad2581e4e5d979f8f970bbee3926f94af9536dbe2ce320
- Size of remote file:
- 329 MB
- SHA256:
- 06e70292124bf09cd889ccbc656ba81d5adcd6a77bda27c7357d316d69310132
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