Text Classification
Transformers
Safetensors
Russian
bert
multilabel-classification
requirements-engineering
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use eternalGenius/rubert_level1_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eternalGenius/rubert_level1_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eternalGenius/rubert_level1_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eternalGenius/rubert_level1_v2") model = AutoModelForSequenceClassification.from_pretrained("eternalGenius/rubert_level1_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Manual update threshold of class Other
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rubert_level1_v2: F1 micro=0.975, F1 macro=0.975
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initial commit
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