Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use marcuscedricridia/distilroberta-fast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcuscedricridia/distilroberta-fast with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcuscedricridia/distilroberta-fast")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcuscedricridia/distilroberta-fast") model = AutoModelForSequenceClassification.from_pretrained("marcuscedricridia/distilroberta-fast", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a338601848a8677394fd0ede2f61ab007eef54f2083513d084cd6b82adc58290
- Size of remote file:
- 5.2 kB
- SHA256:
- d0853e169affac4d3a52d62ff78a09444424d5db78066dddb8c4524cb9654147
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