Instructions to use alenaa/ru_evasiveness with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alenaa/ru_evasiveness with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alenaa/ru_evasiveness")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alenaa/ru_evasiveness") model = AutoModelForSequenceClassification.from_pretrained("alenaa/ru_evasiveness", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Upload BertForSequenceClassification (#3)
- Upload BertForSequenceClassification (9cc11481ba83084b1598f44acebdfff95d07ef08)dababdb -
Upload tokenizer (#2)
- Upload tokenizer (847e330cc3adbe7bade51828eab10c414ef99b82)ef31649 -
Upload BertForSequenceClassification (#1)
- Upload BertForSequenceClassification (f66b996b7037efd5c7d17ab0f3cbe17958ed827e)f233e58 -
initial commit
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