pytorch model
Browse files- 1_Pooling/config.json +7 -0
- README.txt +25 -0
- config.json +3 -0
- modules.json +14 -0
- pytorch_model.bin +3 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
1_Pooling/config.json
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{
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"word_embedding_dimension": 768,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": true,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false
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}
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README.txt
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# cased Finnish Sentence BERT model
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Finnish Sentence BERT trained from FinBERT
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## Training
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FinBERT model: TurkuNLP/bert-base-finnish-cased-v1
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Data: The data provided [here] (https://turkunlp.org/paraphrase.html), including the Finnish Paraphrase Corpus and the automatically collected paraphrase candidates (500K positive and 5M negative)
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Pooling: mean pooling
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Task: Binary prediction, whether two sentences are paraphrases or not. Note: the labels 3 and 4 are considered paraphrases, and labels 1 and 2 non-paraphrases. [Details on labels] (https://aclanthology.org/2021.nodalida-main.29/)
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## Usage
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Please refer to the [HuggingFace documentation] (https://huggingface.co/sentence-transformers/bert-base-nli-mean-tokens)
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Briefly, using the `SentenceTransformer` library,
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```
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from sentence_transformers import SentenceTransformer
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sentences = ["Tämä on esimerkkilause.", "Tämä on toinen lause."]
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model = SentenceTransformer('sbert-cased-finnish-paraphrase')
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embeddings = model.encode(sentences)
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print(embeddings)
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```
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config.json
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{
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"__version__": "0.2.3"
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}
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modules.json
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[
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{
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"idx": 0,
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"name": "0",
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"path": "",
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"type": "sentence_transformers.models.BERT"
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},
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{
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"idx": 1,
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"name": "1",
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"path": "1_Pooling",
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"type": "sentence_transformers.models.Pooling"
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}
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]
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:f1599b1aa408f2ffd35cce5c2e1310c5190b942af976a955765a56ff051f1f50
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size 498140020
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sentence_bert_config.json
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{
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"max_seq_length": 128,
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"do_lower_case": false
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}
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special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer_config.json
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{"do_lower_case": false, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "tokenizer_file": "/users/changlih/.cache/huggingface/transformers/3583dbf83678cb60c5faaf0a07aa0d452fc4ec09aac87b8680027bf79b1a6270.e49785bf2de92e06a4d89026870d6979723c8e64cfc9311596ca5b9a3b56289e", "name_or_path": "TurkuNLP/bert-base-finnish-cased-v1"}
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vocab.txt
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