Instructions to use nasa-impact/bert-e-base-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nasa-impact/bert-e-base-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nasa-impact/bert-e-base-mlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nasa-impact/bert-e-base-mlm") model = AutoModelForMaskedLM.from_pretrained("nasa-impact/bert-e-base-mlm") - Notebooks
- Google Colab
- Kaggle
save as bertmodelformaskedlm rather than automodel
Browse files- config.json +2 -2
- pytorch_model.bin +2 -2
config.json
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"_name_or_path": "allenai/scibert_scivocab_cased",
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"architectures": [
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"BertForMaskedLM"
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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pytorch_model.bin
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size 439969131
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