Small2 but sharded.
Browse filesCreated to test safetensors conversion.
- README.md +1 -0
- config.json +52 -0
- pytorch_model-00001-of-00003.bin +3 -0
- pytorch_model-00002-of-00003.bin +3 -0
- pytorch_model-00003-of-00003.bin +3 -0
- pytorch_model.bin.index.json +47 -0
- roberta.json +0 -0
- special_tokens_map.json +1 -0
- tf_model.h5 +3 -0
- tokenizer_config.json +1 -0
- unigram.model +3 -0
- vocab.txt +0 -0
README.md
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Small change. again. again ? again.
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config.json
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{
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"_name_or_path": "Narsil/small2",
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"_num_labels": 9,
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"architectures": ["BertForTokenClassification"],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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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": 2,
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"id2label": {
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"0": "O",
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"1": "B-MISC",
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"2": "I-MISC",
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"3": "B-PER",
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"4": "I-PER",
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"5": "B-ORG",
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"6": "I-ORG",
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"7": "B-LOC",
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"8": "I-LOC"
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},
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"initializer_range": 0.02,
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"intermediate_size": 4,
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"label2id": {
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"B-LOC": 7,
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"B-MISC": 1,
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"B-ORG": 5,
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"B-PER": 3,
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"I-LOC": 8,
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"I-MISC": 2,
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"I-ORG": 6,
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"I-PER": 4,
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"O": 0
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},
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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": 2,
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"num_hidden_layers": 2,
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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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"transformers_version": "4.10.0.dev0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 28996
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}
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pytorch_model-00001-of-00003.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:f87650c29f497c39f9265f3f8d5cbff82d350d656f17f84211f604773569eb3f
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size 4907
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pytorch_model-00002-of-00003.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:3b2c2f5f27c0ef9e57571711be399b4f6db326d559b66102a5fa9276affafb1e
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size 232747
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pytorch_model-00003-of-00003.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:350be52b37c1248f4df7fc72adf5105202166780689215c2ff1269a33f2ed5ff
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size 15795
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pytorch_model.bin.index.json
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{
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"metadata": {
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"total_size": 240732
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},
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"weight_map": {
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"bert.embeddings.LayerNorm.bias": "pytorch_model-00003-of-00003.bin",
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"bert.embeddings.LayerNorm.weight": "pytorch_model-00003-of-00003.bin",
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"bert.embeddings.position_embeddings.weight": "pytorch_model-00003-of-00003.bin",
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"bert.embeddings.position_ids": "pytorch_model-00001-of-00003.bin",
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"bert.embeddings.token_type_embeddings.weight": "pytorch_model-00003-of-00003.bin",
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"bert.embeddings.word_embeddings.weight": "pytorch_model-00002-of-00003.bin",
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"bert.encoder.layer.0.attention.output.LayerNorm.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.attention.output.LayerNorm.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.attention.output.dense.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.attention.output.dense.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.attention.self.key.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.attention.self.key.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.attention.self.query.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.attention.self.query.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.attention.self.value.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.attention.self.value.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.intermediate.dense.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.intermediate.dense.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.output.LayerNorm.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.output.LayerNorm.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.output.dense.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.0.output.dense.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.attention.output.LayerNorm.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.attention.output.LayerNorm.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.attention.output.dense.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.attention.output.dense.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.attention.self.key.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.attention.self.key.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.attention.self.query.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.attention.self.query.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.attention.self.value.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.attention.self.value.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.intermediate.dense.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.intermediate.dense.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.output.LayerNorm.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.output.LayerNorm.weight": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.output.dense.bias": "pytorch_model-00003-of-00003.bin",
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"bert.encoder.layer.1.output.dense.weight": "pytorch_model-00003-of-00003.bin",
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"classifier.bias": "pytorch_model-00003-of-00003.bin",
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"classifier.weight": "pytorch_model-00003-of-00003.bin"
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}
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}
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roberta.json
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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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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:28422e5654b34d4d92f8675c7b563e01992322451c74cefec9137084ac797766
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size 301400
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tokenizer_config.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "max_len": 512, "special_tokens_map_file": "/home/nicolas/.cache/torch/transformers/7ed0658a09e4f9689057c83f8b734d0e8d739f73461c7b7d1bc403aa451e304b.275045728fbf41c11d3dae08b8742c054377e18d92cc7b72b6351152a99b64e4", "tokenizer_file": null}
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unigram.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:4e6c5a850287ee371b9c2c74ba1c9b10a85ce0436c0e53685903caa635dd2aa3
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size 146491
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vocab.txt
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