Instructions to use MultiBertGunjanPatrick/multiberts-seed-0-140k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MultiBertGunjanPatrick/multiberts-seed-0-140k with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("MultiBertGunjanPatrick/multiberts-seed-0-140k") model = AutoModelForPreTraining.from_pretrained("MultiBertGunjanPatrick/multiberts-seed-0-140k") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): d89a7d0
Fix README
Browse files
README.md
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@@ -3,14 +3,14 @@ language: en
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tags:
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- exbert
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- multiberts
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- multiberts-seed-
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license: apache-2.0
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datasets:
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- bookcorpus
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- wikipedia
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---
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# MultiBERTs Seed 0 Checkpoint 140k (uncased)
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Seed 0 intermediate
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[this paper](https://arxiv.org/pdf/2106.16163.pdf) and first released in
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[this repository](https://github.com/google-research/language/tree/master/language/multiberts). This model is uncased: it does not make a difference
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between english and English.
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tags:
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- exbert
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- multiberts
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- multiberts-seed-1
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license: apache-2.0
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datasets:
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- bookcorpus
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- wikipedia
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---
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# MultiBERTs Seed 0 Checkpoint 140k (uncased)
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+
Seed 0 intermediate checkpoint 140k MultiBERTs (pretrained BERT) model on English language using a masked language modeling (MLM) objective. It was introduced in
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[this paper](https://arxiv.org/pdf/2106.16163.pdf) and first released in
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[this repository](https://github.com/google-research/language/tree/master/language/multiberts). This model is uncased: it does not make a difference
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between english and English.
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