Instructions to use albert/albert-large-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albert/albert-large-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="albert/albert-large-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("albert/albert-large-v2") model = AutoModelForMaskedLM.from_pretrained("albert/albert-large-v2") - Inference
- Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +4 -4
config.json
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@@ -1,7 +1,7 @@
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{
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"attention_probs_dropout_prob": 0
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"hidden_act": "
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"hidden_dropout_prob": 0
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"embedding_size": 128,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"down_scale_factor": 1,
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"type_vocab_size": 2,
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"vocab_size": 30000
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}
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{
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"attention_probs_dropout_prob": 0,
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"hidden_act": "gelu_new",
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"hidden_dropout_prob": 0,
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"embedding_size": 128,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"down_scale_factor": 1,
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"type_vocab_size": 2,
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"vocab_size": 30000
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}
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