simonosgoode
commited on
Commit
•
3a6e85b
1
Parent(s):
04a3c90
Add new SentenceTransformer model.
Browse files- 1_Pooling/config.json +10 -0
- README.md +0 -0
- config.json +58 -0
- config_sentence_transformers.json +10 -0
- configuration_hf_nomic_bert.py +56 -0
- model.safetensors +3 -0
- modules.json +14 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +37 -0
- tokenizer.json +0 -0
- tokenizer_config.json +62 -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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"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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config.json
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{
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"_name_or_path": "models/nomic_finetune2/",
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"activation_function": "swiglu",
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"architectures": [
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"NomicBertModel"
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],
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"attn_pdrop": 0.0,
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"auto_map": {
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"AutoConfig": "configuration_hf_nomic_bert.NomicBertConfig",
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"AutoModel": "nomic-ai/nomic-bert-2048--modeling_hf_nomic_bert.NomicBertModel",
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"AutoModelForMaskedLM": "nomic-ai/nomic-bert-2048--modeling_hf_nomic_bert.NomicBertForPreTraining"
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},
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"bos_token_id": null,
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"causal": false,
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"dense_seq_output": true,
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"embd_pdrop": 0.0,
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"eos_token_id": null,
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"fused_bias_fc": true,
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"fused_dropout_add_ln": true,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-12,
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"max_trained_positions": 2048,
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"mlp_fc1_bias": false,
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"mlp_fc2_bias": false,
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"model_type": "nomic_bert",
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"n_embd": 768,
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"n_head": 12,
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"n_inner": 3072,
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"n_layer": 12,
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"n_positions": 8192,
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"pad_vocab_size_multiple": 64,
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"parallel_block": false,
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"parallel_block_tied_norm": false,
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"prenorm": false,
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"qkv_proj_bias": false,
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"reorder_and_upcast_attn": false,
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"resid_pdrop": 0.0,
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"rotary_emb_base": 1000,
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"rotary_emb_fraction": 1.0,
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"rotary_emb_interleaved": false,
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"rotary_emb_scale_base": null,
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"rotary_scaling_factor": null,
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"scale_attn_by_inverse_layer_idx": false,
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"scale_attn_weights": true,
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"summary_activation": null,
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"summary_first_dropout": 0.0,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"torch_dtype": "float32",
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"transformers_version": "4.45.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"use_flash_attn": true,
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"use_rms_norm": false,
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"use_xentropy": true,
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"vocab_size": 30528
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}
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config_sentence_transformers.json
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{
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"__version__": {
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"sentence_transformers": "3.1.1",
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"transformers": "4.45.2",
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"pytorch": "2.4.1+cu121"
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},
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"prompts": {},
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"default_prompt_name": null,
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"similarity_fn_name": null
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}
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configuration_hf_nomic_bert.py
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from transformers import GPT2Config
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class NomicBertConfig(GPT2Config):
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model_type = "nomic_bert"
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def __init__(
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self,
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prenorm=False,
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parallel_block=False,
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parallel_block_tied_norm=False,
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rotary_emb_fraction=0.0,
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fused_dropout_add_ln=False,
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fused_bias_fc=False,
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use_flash_attn=False,
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use_xentropy=False,
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qkv_proj_bias=True,
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rotary_emb_base=10_000,
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rotary_emb_scale_base=None,
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rotary_emb_interleaved=False,
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mlp_fc1_bias=True,
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mlp_fc2_bias=True,
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use_rms_norm=False,
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causal=False,
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type_vocab_size=2,
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dense_seq_output=True,
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pad_vocab_size_multiple=1,
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tie_word_embeddings=True,
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rotary_scaling_factor=None,
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max_trained_positions=2048,
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**kwargs,
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):
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self.prenorm = prenorm
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self.parallel_block = parallel_block
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self.parallel_block_tied_norm = parallel_block_tied_norm
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self.rotary_emb_fraction = rotary_emb_fraction
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self.tie_word_embeddings = tie_word_embeddings
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self.fused_dropout_add_ln = fused_dropout_add_ln
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self.fused_bias_fc = fused_bias_fc
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self.use_flash_attn = use_flash_attn
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self.use_xentropy = use_xentropy
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self.qkv_proj_bias = qkv_proj_bias
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self.rotary_emb_base = rotary_emb_base
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self.rotary_emb_scale_base = rotary_emb_scale_base
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self.rotary_emb_interleaved = rotary_emb_interleaved
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self.mlp_fc1_bias = mlp_fc1_bias
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self.mlp_fc2_bias = mlp_fc2_bias
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self.use_rms_norm = use_rms_norm
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self.causal = causal
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self.type_vocab_size = type_vocab_size
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self.dense_seq_output = dense_seq_output
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self.pad_vocab_size_multiple = pad_vocab_size_multiple
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self.rotary_scaling_factor = rotary_scaling_factor
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self.max_trained_positions = max_trained_positions
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super().__init__(**kwargs)
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5b839d7a55146cd42fb1419d28cd27f7cfeedcada68b7e053440196d9eab0f3e
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size 546938168
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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.Transformer"
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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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sentence_bert_config.json
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{
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"max_seq_length": 8192,
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"do_lower_case": false
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}
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special_tokens_map.json
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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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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"max_length": 8192,
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"model_max_length": 8192,
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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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