Instructions to use microsoft/deberta-xlarge-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/deberta-xlarge-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="microsoft/deberta-xlarge-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("microsoft/deberta-xlarge-mnli") model = AutoModelForSequenceClassification.from_pretrained("microsoft/deberta-xlarge-mnli", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Pengcheng He commited on
Commit ·
02a79c9
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Parent(s): 29d767f
DeBERTa XLarge MNLI model
Browse files- config.json +4 -0
- pytorch_model.bin +2 -2
config.json
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"num_attention_heads": 16,
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"num_hidden_layers": 48,
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"type_vocab_size": 0,
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"vocab_size": 50265
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}
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"num_attention_heads": 16,
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"num_hidden_layers": 48,
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"type_vocab_size": 0,
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"pooling": {
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"dropout": 0,
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"hidden_act": "gelu"
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},
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"vocab_size": 50265
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}
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pytorch_model.bin
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