Upload 10 files
Browse files- 1_Pooling/config.json +10 -0
- README.md +40 -3
- config.json +31 -0
- mergekit_config.yml +9 -0
- model-00001-of-00001.safetensors +3 -0
- model.safetensors.index.json +1 -0
- special_tokens_map.json +44 -0
- tokenizer.json +0 -0
- tokenizer_config.json +71 -0
- vocab.txt +0 -0
1_Pooling/config.json
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{
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"word_embedding_dimension": 384,
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"pooling_mode_cls_token": true,
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"pooling_mode_mean_tokens": false,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": false,
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"include_prompt": true
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}
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README.md
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---
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---
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base_model:
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- Mihaiii/Wartortle
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- TaylorAI/bge-micro-v2
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library_name: transformers
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tags:
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- mergekit
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- merge
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---
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# Giratina
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the SLERP merge method.
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### Models Merged
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The following models were included in the merge:
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* [Mihaiii/Wartortle](https://huggingface.co/Mihaiii/Wartortle)
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* [TaylorAI/bge-micro-v2](https://huggingface.co/TaylorAI/bge-micro-v2)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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models:
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- model: Mihaiii/Wartortle
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- model: TaylorAI/bge-micro-v2
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merge_method: slerp
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base_model: TaylorAI/bge-micro-v2
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parameters:
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t:
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- value: 0.5
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dtype: float32
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```
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config.json
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{
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"_name_or_path": "TaylorAI/bge-micro-v2",
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"architectures": [
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"BertModel"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 384,
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"id2label": {
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"0": "LABEL_0"
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},
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"initializer_range": 0.02,
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"intermediate_size": 1536,
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"label2id": {
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"LABEL_0": 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": 12,
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"num_hidden_layers": 3,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.40.1",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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mergekit_config.yml
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models:
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- model: Mihaiii/Wartortle
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- model: TaylorAI/bge-micro-v2
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merge_method: slerp
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base_model: TaylorAI/bge-micro-v2
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parameters:
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t:
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- value: 0.5
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dtype: float32
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model-00001-of-00001.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:a09588892630ea4670f4cfa9be2f3486bfc2543e94e2638591c4fa526ef5585c
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size 69565312
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model.safetensors.index.json
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{"metadata": {"mergekit_version": "0.0.4.2", "total_size": 69559296}, "weight_map": {"embeddings.LayerNorm.bias": "model-00001-of-00001.safetensors", "embeddings.LayerNorm.weight": "model-00001-of-00001.safetensors", "embeddings.position_embeddings.weight": "model-00001-of-00001.safetensors", "embeddings.token_type_embeddings.weight": "model-00001-of-00001.safetensors", "embeddings.word_embeddings.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.output.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.self.key.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.self.key.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.self.query.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.self.query.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.self.value.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.self.value.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.intermediate.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.intermediate.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.output.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.output.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.self.key.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.self.key.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.self.query.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.self.query.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.self.value.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.self.value.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.intermediate.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.intermediate.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.output.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.output.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.self.key.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.self.key.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.self.query.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.self.query.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.self.value.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.self.value.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.intermediate.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.intermediate.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.output.dense.weight": "model-00001-of-00001.safetensors", "pooler.dense.bias": "model-00001-of-00001.safetensors", "pooler.dense.weight": "model-00001-of-00001.safetensors"}}
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special_tokens_map.json
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{
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"additional_special_tokens": [
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"[PAD]",
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"[UNK]",
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"[CLS]",
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"[SEP]",
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"[MASK]"
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],
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"cls_token": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"mask_token": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"sep_token": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"100": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"101": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"102": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"103": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"additional_special_tokens": [
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"[PAD]",
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"[UNK]",
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"[CLS]",
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"[SEP]",
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"[MASK]"
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],
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"max_length": 512,
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"model_max_length": 1000000000000000019884624838656,
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"never_split": null,
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"pad_to_multiple_of": null,
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"pad_token": "[PAD]",
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"pad_token_type_id": 0,
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"padding_side": "right",
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"sep_token": "[SEP]",
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"stride": 0,
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"truncation_side": "right",
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"truncation_strategy": "longest_first",
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"unk_token": "[UNK]"
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}
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vocab.txt
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