Instructions to use dl-ru/rubert-tiny2-srl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dl-ru/rubert-tiny2-srl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dl-ru/rubert-tiny2-srl")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dl-ru/rubert-tiny2-srl") model = AutoModelForTokenClassification.from_pretrained("dl-ru/rubert-tiny2-srl") - Notebooks
- Google Colab
- Kaggle
Next version
Browse files- config.json +3 -1
- pytorch_model.bin +2 -2
- training_args.bin +1 -1
config.json
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"5": "B-Deliberative",
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"6": "B-Causator",
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"7": "B-ContrSubject",
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"8": "B-Benefactive"
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},
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"initializer_range": 0.02,
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"intermediate_size": 600,
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"label2id": {
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"B-Benefactive": 8,
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"B-Causator": 6,
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"B-Cause": 4,
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"5": "B-Deliberative",
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"6": "B-Causator",
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"7": "B-ContrSubject",
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"8": "B-Benefactive",
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"9": "B-Addressee"
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},
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"initializer_range": 0.02,
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"intermediate_size": 600,
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"label2id": {
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"B-Addressee": 9,
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"B-Benefactive": 8,
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"B-Causator": 6,
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"B-Cause": 4,
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pytorch_model.bin
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training_args.bin
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