Instructions to use DeepPavlov/roberta-large-winogrande with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepPavlov/roberta-large-winogrande with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DeepPavlov/roberta-large-winogrande")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DeepPavlov/roberta-large-winogrande") model = AutoModelForSequenceClassification.from_pretrained("DeepPavlov/roberta-large-winogrande", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +9 -1
config.json
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "roberta",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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}
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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"0": "False",
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"1": "True"
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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"False": 0,
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"True": 1
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "roberta",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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}
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