fuliucansheng commited on
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  ./clr/pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
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  ./clr/pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
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  ./detection/PascalVOC_Detection/pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
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+ ./culr/pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
culr/README.md ADDED
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+ ## 9/13/2021
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+ Junyi: repackage CULRv2 using config from InfoXLM from Huggingface as these two models are the same
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+
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+ # InfoXLM
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+
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+ **InfoXLM** (NAACL 2021, [paper](https://arxiv.org/pdf/2007.07834.pdf), [repo](https://github.com/microsoft/unilm/tree/master/infoxlm), [model](https://huggingface.co/microsoft/infoxlm-base)) InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training.
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+
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+ **MD5**
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+
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+ ```
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+ 05b95b7d977450b364f8ea3269391953 config.json
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+ c19438359fed6d36b0c1bbb107929579 pytorch_model.bin
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+ bf25eb5120ad92ef5c7d8596b5dc4046 sentencepiece.bpe.model
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+ eedbd60a7268b9fc45981b849664f747 tokenizer.json
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+ ```
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+
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+ **BibTeX**
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+
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+ ```
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+ @inproceedings{chi-etal-2021-infoxlm,
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+ title = "{I}nfo{XLM}: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training",
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+ author={Chi, Zewen and Dong, Li and Wei, Furu and Yang, Nan and Singhal, Saksham and Wang, Wenhui and Song, Xia and Mao, Xian-Ling and Huang, Heyan and Zhou, Ming},
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+ booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
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+ month = jun,
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+ year = "2021",
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+ address = "Online",
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+ publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/2021.naacl-main.280",
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+ doi = "10.18653/v1/2021.naacl-main.280",
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+ pages = "3576--3588",}
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+ ```
culr/config.json ADDED
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+ {
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+ "architectures": [
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+ "XLMRobertaForMaskedLM"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "bos_token_id": 0,
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+ "eos_token_id": 2,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 1024,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 4096,
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 514,
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+ "model_type": "xlm-roberta",
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+ "num_attention_heads": 16,
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+ "num_hidden_layers": 24,
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+ "output_past": true,
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+ "pad_token_id": 1,
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+ "type_vocab_size": 1,
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+ "vocab_size": 250008
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+ }
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