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  1. README.md +54 -0
  2. config.json +28 -0
  3. pytorch_model.bin +3 -0
  4. tf_model.h5 +3 -0
  5. tokenizer_config.json +1 -0
  6. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ language: multilingual
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+
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+ datasets: wikipedia
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+
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+ license: apache-2.0
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+
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+ widget:
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+ - text: "Google generated 46 billion [MASK] in revenue."
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+ - text: "Paris is the capital of [MASK]."
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+ - text: "Algiers is the largest city in [MASK]."
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+ - text: "Paris est la [MASK] de la France."
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+ - text: "Paris est la capitale de la [MASK]."
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+ - text: "L'élection américaine a eu [MASK] en novembre 2020."
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+ - text: "تقع سويسرا في [MASK] أوروبا"
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+ - text: "إسمي محمد وأسكن في [MASK]."
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+ ---
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+
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+ # bert-base-10lang-cased
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+
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+ We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.
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+
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+ Unlike [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.
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+
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+ This model handles the following languages: english, french, spanish, german, chinese, arabic, russian, portuguese, italian, and urdu. It produces the same representations as [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) while being 22.5% smaller in size.
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+
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+ For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).
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+
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+ ## How to use
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+
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+ ```python
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+ from transformers import AutoTokenizer, AutoModel
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+
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+ tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-10lang-cased")
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+ model = AutoModel.from_pretrained("Geotrend/bert-base-10lang-cased")
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+
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+ ```
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+
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+ To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).
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+
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+ ### How to cite
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+
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+ ```bibtex
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+ @inproceedings{smallermbert,
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+ title={Load What You Need: Smaller Versions of Multilingual BERT},
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+ author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire},
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+ booktitle={SustaiNLP / EMNLP},
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+ year={2020}
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+ }
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+ ```
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+
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+ ## Contact
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+
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+ Please contact amine@geotrend.fr for any question, feedback or request.
config.json ADDED
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+ {
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+ "_name_or_path": "new-models/bert-base-10lang-cased",
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+ "architectures": [
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+ "BertForMaskedLM"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "directionality": "bidi",
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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+ "position_embedding_type": "absolute",
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+ "type_vocab_size": 2,
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+ "vocab_size": 67318
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+ }
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vocab.txt ADDED
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