Instructions to use martincc98/bert_a3_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use martincc98/bert_a3_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="martincc98/bert_a3_2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("martincc98/bert_a3_2") model = AutoModelForMaskedLM.from_pretrained("martincc98/bert_a3_2") - Notebooks
- Google Colab
- Kaggle
Upload config
Browse files- config.json +1 -2
config.json
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"_name_or_path": "distilbert-base-uncased",
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"activation": "gelu",
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"architectures": [
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"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.44.2",
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"vocab_size": 30522
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}
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"_name_or_path": "distilbert-base-uncased",
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"activation": "gelu",
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"architectures": [
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"DistilBertForMaskedLM"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"transformers_version": "4.44.2",
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"vocab_size": 30522
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}
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