Instructions to use magicslabnu/OutEffHop_bert_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use magicslabnu/OutEffHop_bert_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="magicslabnu/OutEffHop_bert_base", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("magicslabnu/OutEffHop_bert_base", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("magicslabnu/OutEffHop_bert_base", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +2 -1
config.json
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@@ -10,6 +10,7 @@
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"AutoModelForSequenceClassification": "modeling_bert.BertForSequenceClassification"
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},
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"transformers_version": "4.31.0",
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"type_vocab_size": 2,
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"use_cache": true,
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-
"vocab_size": 30522
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}
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"AutoModelForSequenceClassification": "modeling_bert.BertForSequenceClassification"
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},
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"attention_probs_dropout_prob": 0.1,
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+
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"transformers_version": "4.31.0",
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"type_vocab_size": 2,
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"use_cache": true,
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+
"vocab_size": 30522
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}
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