Instructions to use Rustem/roberta-base-best with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rustem/roberta-base-best with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Rustem/roberta-base-best")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Rustem/roberta-base-best") model = AutoModelForSequenceClassification.from_pretrained("Rustem/roberta-base-best", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Upload pytorch_model.bin with git-lfs
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Upload config.json
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Upload CEBinaryAccuracyEvaluator_ValidationB_results.csv
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Upload merges.txt
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Upload tokenizer_config.json
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initial commit
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