first init
Browse files- added_tokens.json +44 -0
- config.json +380 -0
- generation_config.json +4 -0
- pytorch_model-00001-of-00011.bin +3 -0
- pytorch_model-00002-of-00011.bin +3 -0
- pytorch_model-00003-of-00011.bin +3 -0
- pytorch_model-00004-of-00011.bin +3 -0
- pytorch_model-00005-of-00011.bin +3 -0
- pytorch_model-00006-of-00011.bin +3 -0
- pytorch_model-00007-of-00011.bin +3 -0
- pytorch_model-00008-of-00011.bin +3 -0
- pytorch_model-00009-of-00011.bin +3 -0
- pytorch_model-00010-of-00011.bin +3 -0
- pytorch_model-00011-of-00011.bin +3 -0
- pytorch_model.bin.index.json +0 -0
- special_tokens_map.json +50 -0
- tokenization_internlm2.py +235 -0
- tokenizer.model +3 -0
- tokenizer_config.json +400 -0
added_tokens.json
ADDED
@@ -0,0 +1,44 @@
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{
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"</box>": 92552,
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"</det>": 92560,
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"</grd>": 92562,
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"</img>": 92545,
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"</quad>": 92548,
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"</ref>": 92550,
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"</reg>": 92558,
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"</s>": 2,
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"<IMG_CONTEXT>": 92546,
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"<box>": 92551,
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"<det>": 92559,
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"<grd>": 92561,
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"<im_patch>": 92555,
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"<image>": 92554,
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"<img>": 92544,
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"<quad>": 92547,
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"<ref>": 92549,
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"<reg>": 92557,
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"<region>": 92556,
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"<s>": 1,
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"<unk>": 0,
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"<|action_end|>": 92540,
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"<|action_start|>": 92541,
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"<|im_end|>": 92542,
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"<|im_start|>": 92543,
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"<|interpreter|>": 92539,
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"<|plugin|>": 92538,
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"[DET]": 92563,
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"[EDIT]": 92568,
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"[EMB2]": 92570,
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"[EMB3]": 92571,
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"[EMB4]": 92572,
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"[EMB5]": 92573,
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"[EMB6]": 92574,
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"[EMB7]": 92575,
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"[EMB8]": 92576,
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"[EMB]": 92569,
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"[GEN]": 92567,
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"[GRD]": 92564,
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"[PAD]": 92553,
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"[POSE]": 92566,
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"[SEG]": 92565
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}
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config.json
ADDED
@@ -0,0 +1,380 @@
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+
{
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2 |
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"_commit_hash": null,
|
3 |
+
"_name_or_path": "work_dirs/internvl-gen-edit-1epoch/bak/checkpoint-14000",
|
4 |
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"architectures": [
|
5 |
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"VisionLLMv2Model"
|
6 |
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],
|
7 |
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"gdino_config": null,
|
8 |
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"ip2p_config": {
|
9 |
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"_name_or_path": "visionllmv2/model/instruct_pix2pix/ip2p.json",
|
10 |
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"add_cross_attention": false,
|
11 |
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"architectures": [
|
12 |
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"InstructPix2PixWithLLMEmbConfig"
|
13 |
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],
|
14 |
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"bad_words_ids": null,
|
15 |
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"begin_suppress_tokens": null,
|
16 |
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"bos_token_id": null,
|
17 |
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"cfg_drop_rate": 0.05,
|
18 |
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"cfg_scale": 7.5,
|
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"chunk_size_feed_forward": 0,
|
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"cross_attention_hidden_size": null,
|
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"decoder_start_token_id": null,
|
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"diversity_penalty": 0.0,
|
23 |
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"do_sample": false,
|
24 |
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"early_stopping": false,
|
25 |
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"embed_tokens": {
|
26 |
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"emb": "[EMB]",
|
27 |
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"emb2": "[EMB2]",
|
28 |
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"emb3": "[EMB3]",
|
29 |
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"emb4": "[EMB4]",
|
30 |
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"emb5": "[EMB5]",
|
31 |
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"emb6": "[EMB6]",
|
32 |
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"emb7": "[EMB7]",
|
33 |
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"emb8": "[EMB8]"
|
34 |
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},
|
35 |
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"encoder_no_repeat_ngram_size": 0,
|
36 |
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"eos_token_id": null,
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"exponential_decay_length_penalty": null,
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"finetuning_task": null,
|
39 |
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"forced_bos_token_id": null,
|
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"forced_eos_token_id": null,
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41 |
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"id2label": {
|
42 |
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"0": "LABEL_0",
|
43 |
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"1": "LABEL_1"
|
44 |
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"is_decoder": false,
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"is_encoder_decoder": false,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1
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"length_penalty": 1.0,
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"llm_hidden_size": 6144,
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"max_length": 20,
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"min_length": 0,
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"model_type": "instructpix2pix_with_llm_emb",
|
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"no_repeat_ngram_size": 0,
|
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"num_beam_groups": 1,
|
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"num_beams": 1,
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"num_decoder_layers": 1,
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"num_embed_tokens": 64,
|
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"num_encoder_layers": 1,
|
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"num_queries": 77,
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"num_return_sequences": 1,
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"output_attentions": false,
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|
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"output_scores": false,
|
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"pad_token_id": null,
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"prefix": null,
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"problem_type": null,
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"pruned_heads": {},
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"return_dict": true,
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"return_dict_in_generate": false,
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"sd_hidden_size": 768,
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"sd_model_id": "checkpoints/instruct-pix2pix",
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"sep_token_id": null,
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|
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"temperature": 1.0,
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"tf_legacy_loss": false,
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"tie_word_embeddings": true,
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"tokenizer_class": null,
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"top_k": 50,
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"top_p": 1.0,
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"torch_dtype": null,
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"torchscript": false,
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"transformers_version": "4.34.0",
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"trigger_token": "[EDIT]",
|
91 |
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"trigger_token_id": 92568,
|
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"typical_p": 1.0,
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"use_bfloat16": false
|
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},
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"l_hidden_size": 6144,
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"llm_config": {
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"_name_or_path": "pretrained/internlm2-chat-20b/",
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"add_cross_attention": false,
|
99 |
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"architectures": [
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100 |
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"InternLM2ForCausalLM"
|
101 |
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],
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102 |
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"attention_bias": false,
|
103 |
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"attn_implementation": "flash_attention_2",
|
104 |
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"auto_map": {
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105 |
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"AutoConfig": "configuration_internlm2.InternLM2Config",
|
106 |
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"AutoModel": "modeling_internlm2.InternLM2ForCausalLM",
|
107 |
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"AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM"
|
108 |
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},
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109 |
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"bad_words_ids": null,
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110 |
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"begin_suppress_tokens": null,
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111 |
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"bias": false,
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"bos_token_id": 1,
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"chunk_size_feed_forward": 0,
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"cross_attention_hidden_size": null,
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123 |
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|
125 |
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"hidden_act": "silu",
|
126 |
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"hidden_size": 6144,
|
127 |
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"id2label": {
|
128 |
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"0": "LABEL_0",
|
129 |
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|
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131 |
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"initializer_range": 0.02,
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132 |
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"intermediate_size": 16384,
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141 |
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"max_position_embeddings": 32768,
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|
143 |
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"model_type": "llama",
|
144 |
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161 |
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165 |
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|
166 |
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172 |
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177 |
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178 |
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179 |
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|
180 |
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181 |
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182 |
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183 |
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184 |
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185 |
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186 |
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|
187 |
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|
188 |
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|
189 |
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"num_embs_gen": 64,
|
190 |
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|
191 |
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"sd_config": {
|
192 |
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|
193 |
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"add_cross_attention": false,
|
194 |
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"architectures": [
|
195 |
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"StableDiffusionWithLLMEmbConfig"
|
196 |
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|
197 |
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|
198 |
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|
199 |
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|
200 |
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|
201 |
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|
202 |
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203 |
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204 |
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# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved.
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+
#
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# This code is based on transformers/src/transformers/models/llama/tokenization_llama.py
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+
#
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+
# Licensed under the Apache License, Version 2.0 (the "License");
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+
# you may not use this file except in compliance with the License.
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+
# You may obtain a copy of the License at
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+
#
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+
# http://www.apache.org/licenses/LICENSE-2.0
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+
#
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+
# Unless required by applicable law or agreed to in writing, software
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+
# distributed under the License is distributed on an "AS IS" BASIS,
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+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+
# See the License for the specific language governing permissions and
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+
# limitations under the License.
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+
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+
"""Tokenization classes for InternLM."""
|
18 |
+
import os
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19 |
+
from shutil import copyfile
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20 |
+
from typing import Any, Dict, List, Optional, Tuple
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21 |
+
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22 |
+
import sentencepiece as spm
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23 |
+
from transformers.tokenization_utils import PreTrainedTokenizer
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24 |
+
from transformers.utils import logging
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25 |
+
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26 |
+
logger = logging.get_logger(__name__)
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27 |
+
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+
VOCAB_FILES_NAMES = {'vocab_file': './tokenizer.model'}
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29 |
+
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30 |
+
PRETRAINED_VOCAB_FILES_MAP = {}
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31 |
+
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+
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+
# Modified from transformers.model.llama.tokenization_llama.LlamaTokenizer
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34 |
+
class InternLM2Tokenizer(PreTrainedTokenizer):
|
35 |
+
"""
|
36 |
+
Construct a InternLM2 tokenizer. Based on byte-level Byte-Pair-Encoding.
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37 |
+
|
38 |
+
Args:
|
39 |
+
vocab_file (`str`):
|
40 |
+
Path to the vocabulary file.
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41 |
+
"""
|
42 |
+
|
43 |
+
vocab_files_names = VOCAB_FILES_NAMES
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44 |
+
pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP
|
45 |
+
model_input_names = ['input_ids', 'attention_mask']
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46 |
+
_auto_class = 'AutoTokenizer'
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47 |
+
|
48 |
+
def __init__(
|
49 |
+
self,
|
50 |
+
vocab_file,
|
51 |
+
unk_token='<unk>',
|
52 |
+
bos_token='<s>',
|
53 |
+
eos_token='</s>',
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54 |
+
pad_token='</s>',
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55 |
+
sp_model_kwargs: Optional[Dict[str, Any]] = None,
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56 |
+
add_bos_token=True,
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57 |
+
add_eos_token=False,
|
58 |
+
decode_with_prefix_space=False,
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59 |
+
clean_up_tokenization_spaces=False,
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60 |
+
**kwargs,
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61 |
+
):
|
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+
self.sp_model_kwargs = {} if sp_model_kwargs is None else sp_model_kwargs
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63 |
+
self.vocab_file = vocab_file
|
64 |
+
self.add_bos_token = add_bos_token
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+
self.add_eos_token = add_eos_token
|
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+
self.decode_with_prefix_space = decode_with_prefix_space
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+
self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs)
|
68 |
+
self.sp_model.Load(vocab_file)
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+
self._no_prefix_space_tokens = None
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+
super().__init__(
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71 |
+
bos_token=bos_token,
|
72 |
+
eos_token=eos_token,
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73 |
+
unk_token=unk_token,
|
74 |
+
pad_token=pad_token,
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75 |
+
clean_up_tokenization_spaces=clean_up_tokenization_spaces,
|
76 |
+
**kwargs,
|
77 |
+
)
|
78 |
+
|
79 |
+
@property
|
80 |
+
def no_prefix_space_tokens(self):
|
81 |
+
if self._no_prefix_space_tokens is None:
|
82 |
+
vocab = self.convert_ids_to_tokens(list(range(self.vocab_size)))
|
83 |
+
self._no_prefix_space_tokens = {i for i, tok in enumerate(vocab) if not tok.startswith('▁')}
|
84 |
+
return self._no_prefix_space_tokens
|
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+
|
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+
@property
|
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+
def vocab_size(self):
|
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+
"""Returns vocab size"""
|
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+
return self.sp_model.get_piece_size()
|
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+
|
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+
@property
|
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+
def bos_token_id(self) -> Optional[int]:
|
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+
return self.sp_model.bos_id()
|
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+
|
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+
@property
|
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+
def eos_token_id(self) -> Optional[int]:
|
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+
return self.sp_model.eos_id()
|
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+
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+
def get_vocab(self):
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+
"""Returns vocab as a dict"""
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+
vocab = {self.convert_ids_to_tokens(i): i for i in range(self.vocab_size)}
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102 |
+
vocab.update(self.added_tokens_encoder)
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103 |
+
return vocab
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+
|
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+
def _tokenize(self, text):
|
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+
"""Returns a tokenized string."""
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+
return self.sp_model.encode(text, out_type=str)
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+
|
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+
def _convert_token_to_id(self, token):
|
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+
"""Converts a token (str) in an id using the vocab."""
|
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+
return self.sp_model.piece_to_id(token)
|
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+
|
113 |
+
def _convert_id_to_token(self, index):
|
114 |
+
"""Converts an index (integer) in a token (str) using the vocab."""
|
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+
token = self.sp_model.IdToPiece(index)
|
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+
return token
|
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+
|
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+
def _maybe_add_prefix_space(self, tokens, decoded):
|
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+
if tokens and tokens[0] not in self.no_prefix_space_tokens:
|
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+
return ' ' + decoded
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+
else:
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+
return decoded
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+
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+
def convert_tokens_to_string(self, tokens):
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+
"""Converts a sequence of tokens (string) in a single string."""
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+
current_sub_tokens = []
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+
out_string = ''
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+
prev_is_special = False
|
129 |
+
for token in tokens:
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+
# make sure that special tokens are not decoded using sentencepiece model
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+
if token in self.all_special_tokens:
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132 |
+
if not prev_is_special:
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+
out_string += ' '
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+
out_string += self.sp_model.decode(current_sub_tokens) + token
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+
prev_is_special = True
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+
current_sub_tokens = []
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+
else:
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+
current_sub_tokens.append(token)
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+
prev_is_special = False
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+
out_string += self.sp_model.decode(current_sub_tokens)
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+
out_string = self.clean_up_tokenization(out_string)
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+
out_string = self._maybe_add_prefix_space(tokens=tokens, decoded=out_string)
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+
return out_string[1:]
|
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+
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+
def save_vocabulary(self, save_directory, filename_prefix: Optional[str] = None) -> Tuple[str]:
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+
"""
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+
Save the vocabulary and special tokens file to a directory.
|
148 |
+
|
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+
Args:
|
150 |
+
save_directory (`str`):
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151 |
+
The directory in which to save the vocabulary.
|
152 |
+
|
153 |
+
Returns:
|
154 |
+
`Tuple(str)`: Paths to the files saved.
|
155 |
+
"""
|
156 |
+
if not os.path.isdir(save_directory):
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157 |
+
logger.error(f'Vocabulary path ({save_directory}) should be a directory')
|
158 |
+
return
|
159 |
+
out_vocab_file = os.path.join(
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160 |
+
save_directory, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']
|
161 |
+
)
|
162 |
+
|
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+
if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file) and os.path.isfile(self.vocab_file):
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164 |
+
copyfile(self.vocab_file, out_vocab_file)
|
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+
elif not os.path.isfile(self.vocab_file):
|
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+
with open(out_vocab_file, 'wb') as fi:
|
167 |
+
content_spiece_model = self.sp_model.serialized_model_proto()
|
168 |
+
fi.write(content_spiece_model)
|
169 |
+
|
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+
return (out_vocab_file,)
|
171 |
+
|
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+
def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None):
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173 |
+
if self.add_bos_token:
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+
bos_token_ids = [self.bos_token_id]
|
175 |
+
else:
|
176 |
+
bos_token_ids = []
|
177 |
+
|
178 |
+
output = bos_token_ids + token_ids_0
|
179 |
+
|
180 |
+
if token_ids_1 is not None:
|
181 |
+
output = output + token_ids_1
|
182 |
+
|
183 |
+
if self.add_eos_token:
|
184 |
+
output = output + [self.eos_token_id]
|
185 |
+
|
186 |
+
return output
|
187 |
+
|
188 |
+
def get_special_tokens_mask(
|
189 |
+
self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None, already_has_special_tokens: bool = False
|
190 |
+
) -> List[int]:
|
191 |
+
"""
|
192 |
+
Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding
|
193 |
+
special tokens using the tokenizer `prepare_for_model` method.
|
194 |
+
|
195 |
+
Args:
|
196 |
+
token_ids_0 (`List[int]`):
|
197 |
+
List of IDs.
|
198 |
+
token_ids_1 (`List[int]`, *optional*):
|
199 |
+
Optional second list of IDs for sequence pairs.
|
200 |
+
already_has_special_tokens (`bool`, *optional*, defaults to `False`):
|
201 |
+
Whether or not the token list is already formatted with special tokens for the model.
|
202 |
+
|
203 |
+
Returns:
|
204 |
+
`List[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token.
|
205 |
+
"""
|
206 |
+
if already_has_special_tokens:
|
207 |
+
return super().get_special_tokens_mask(
|
208 |
+
token_ids_0=token_ids_0, token_ids_1=token_ids_1, already_has_special_tokens=True
|
209 |
+
)
|
210 |
+
|
211 |
+
if token_ids_1 is None:
|
212 |
+
return [1] + ([0] * len(token_ids_0)) + [1]
|
213 |
+
return [1] + ([0] * len(token_ids_0)) + [1, 1] + ([0] * len(token_ids_1)) + [1]
|
214 |
+
|
215 |
+
def create_token_type_ids_from_sequences(
|
216 |
+
self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None
|
217 |
+
) -> List[int]:
|
218 |
+
"""
|
219 |
+
Create a mask from the two sequences passed to be used in a sequence-pair classification task. T5 does not make
|
220 |
+
use of token type ids, therefore a list of zeros is returned.
|
221 |
+
|
222 |
+
Args:
|
223 |
+
token_ids_0 (`List[int]`):
|
224 |
+
List of IDs.
|
225 |
+
token_ids_1 (`List[int]`, *optional*):
|
226 |
+
Optional second list of IDs for sequence pairs.
|
227 |
+
|
228 |
+
Returns:
|
229 |
+
`List[int]`: List of zeros.
|
230 |
+
"""
|
231 |
+
eos = [self.eos_token_id]
|
232 |
+
|
233 |
+
if token_ids_1 is None:
|
234 |
+
return len(token_ids_0 + eos) * [0]
|
235 |
+
return len(token_ids_0 + eos + token_ids_1 + eos) * [0]
|
tokenizer.model
ADDED
@@ -0,0 +1,3 @@
|
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|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f868398fc4e05ee1e8aeba95ddf18ddcc45b8bce55d5093bead5bbf80429b48b
|
3 |
+
size 1477754
|
tokenizer_config.json
ADDED
@@ -0,0 +1,400 @@
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|
|
|
1 |
+
{
|
2 |
+
"added_tokens_decoder": {
|
3 |
+
"0": {
|
4 |
+
"content": "<unk>",
|
5 |
+
"lstrip": false,
|
6 |
+
"normalized": false,
|
7 |
+
"rstrip": false,
|
8 |
+
"single_word": false,
|
9 |
+
"special": true
|
10 |
+
},
|
11 |
+
"1": {
|
12 |
+
"content": "<s>",
|
13 |
+
"lstrip": false,
|
14 |
+
"normalized": false,
|
15 |
+
"rstrip": false,
|
16 |
+
"single_word": false,
|
17 |
+
"special": true
|
18 |
+
},
|
19 |
+
"2": {
|
20 |
+
"content": "</s>",
|
21 |
+
"lstrip": false,
|
22 |
+
"normalized": false,
|
23 |
+
"rstrip": false,
|
24 |
+
"single_word": false,
|
25 |
+
"special": true
|
26 |
+
},
|
27 |
+
"92538": {
|
28 |
+
"content": "<|plugin|>",
|
29 |
+
"lstrip": false,
|
30 |
+
"normalized": false,
|
31 |
+
"rstrip": false,
|
32 |
+
"single_word": false,
|
33 |
+
"special": true
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},
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},
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|
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|
110 |
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|
111 |
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|
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|
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},
|
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|
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"content": "<ref>",
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|
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},
|
123 |
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|
124 |
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"content": "</ref>",
|
125 |
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|
126 |
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|
127 |
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|
128 |
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|
129 |
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|
130 |
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},
|
131 |
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|
132 |
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"content": "<box>",
|
133 |
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|
134 |
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|
135 |
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|
136 |
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|
137 |
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"special": true
|
138 |
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},
|
139 |
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|
140 |
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"content": "</box>",
|
141 |
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|
142 |
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|
143 |
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|
144 |
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|
145 |
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"special": true
|
146 |
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},
|
147 |
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|
148 |
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"content": "[PAD]",
|
149 |
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"lstrip": true,
|
150 |
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|
151 |
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|
152 |
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|
153 |
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"special": true
|
154 |
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},
|
155 |
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"92554": {
|
156 |
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"content": "<image>",
|
157 |
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"lstrip": true,
|
158 |
+
"normalized": false,
|
159 |
+
"rstrip": true,
|
160 |
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|
161 |
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"special": true
|
162 |
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},
|
163 |
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"92555": {
|
164 |
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"content": "<im_patch>",
|
165 |
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"lstrip": true,
|
166 |
+
"normalized": false,
|
167 |
+
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|
168 |
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|
169 |
+
"special": true
|
170 |
+
},
|
171 |
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"92556": {
|
172 |
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"content": "<region>",
|
173 |
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"lstrip": true,
|
174 |
+
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|
175 |
+
"rstrip": true,
|
176 |
+
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|
177 |
+
"special": true
|
178 |
+
},
|
179 |
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"92557": {
|
180 |
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"content": "<reg>",
|
181 |
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"lstrip": true,
|
182 |
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|
183 |
+
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|
184 |
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|
185 |
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|
186 |
+
},
|
187 |
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|
188 |
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"content": "</reg>",
|
189 |
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|
190 |
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|
191 |
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|
192 |
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|
193 |
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194 |
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},
|
195 |
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|
196 |
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197 |
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|
198 |
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|
199 |
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|
200 |
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|
201 |
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202 |
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},
|
203 |
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|
204 |
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"content": "</det>",
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205 |
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206 |
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|
207 |
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|
208 |
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|
209 |
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210 |
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},
|
211 |
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212 |
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"content": "<grd>",
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213 |
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214 |
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|
215 |
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|
216 |
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|
217 |
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|
218 |
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},
|
219 |
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"92562": {
|
220 |
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"content": "</grd>",
|
221 |
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|
222 |
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|
223 |
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|
224 |
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|
225 |
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226 |
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},
|
227 |
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"92563": {
|
228 |
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"content": "[DET]",
|
229 |
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|
230 |
+
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|
231 |
+
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|
232 |
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|
233 |
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|
234 |
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},
|
235 |
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"92564": {
|
236 |
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"content": "[GRD]",
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237 |
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|
238 |
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|
239 |
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|
240 |
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|
241 |
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|
242 |
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},
|
243 |
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|
244 |
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"content": "[SEG]",
|
245 |
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|
246 |
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|
247 |
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|
248 |
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|
249 |
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|
250 |
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},
|
251 |
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|
252 |
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"content": "[POSE]",
|
253 |
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|
254 |
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|
255 |
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256 |
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|
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258 |
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|
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|
260 |
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|
261 |
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|
262 |
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|
263 |
+
"rstrip": true,
|
264 |
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|
265 |
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|
266 |
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},
|
267 |
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|
268 |
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"content": "[EDIT]",
|
269 |
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|
270 |
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|
271 |
+
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|
272 |
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|
273 |
+
"special": true
|
274 |
+
},
|
275 |
+
"92569": {
|
276 |
+
"content": "[EMB]",
|
277 |
+
"lstrip": true,
|
278 |
+
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|
279 |
+
"rstrip": true,
|
280 |
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|
281 |
+
"special": true
|
282 |
+
},
|
283 |
+
"92570": {
|
284 |
+
"content": "[EMB2]",
|
285 |
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|
286 |
+
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|
287 |
+
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|
288 |
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|
289 |
+
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|
290 |
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},
|
291 |
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|
292 |
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"content": "[EMB3]",
|
293 |
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"lstrip": true,
|
294 |
+
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|
295 |
+
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|
296 |
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|
297 |
+
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|
298 |
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},
|
299 |
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|
300 |
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"content": "[EMB4]",
|
301 |
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|
302 |
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|
303 |
+
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|
304 |
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|
305 |
+
"special": true
|
306 |
+
},
|
307 |
+
"92573": {
|
308 |
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"content": "[EMB5]",
|
309 |
+
"lstrip": true,
|
310 |
+
"normalized": false,
|
311 |
+
"rstrip": true,
|
312 |
+
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|
313 |
+
"special": true
|
314 |
+
},
|
315 |
+
"92574": {
|
316 |
+
"content": "[EMB6]",
|
317 |
+
"lstrip": true,
|
318 |
+
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|
319 |
+
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|
320 |
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|
321 |
+
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|
322 |
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},
|
323 |
+
"92575": {
|
324 |
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"content": "[EMB7]",
|
325 |
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"lstrip": true,
|
326 |
+
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|
327 |
+
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|
328 |
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|
329 |
+
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|
330 |
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},
|
331 |
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|
332 |
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|
333 |
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|
334 |
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|
335 |
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|
336 |
+
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|
337 |
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|
338 |
+
}
|
339 |
+
},
|
340 |
+
"additional_special_tokens": [
|
341 |
+
"<unk>",
|
342 |
+
"<s>",
|
343 |
+
"</s>",
|
344 |
+
"<|plugin|>",
|
345 |
+
"<|interpreter|>",
|
346 |
+
"<|action_end|>",
|
347 |
+
"<|action_start|>",
|
348 |
+
"<|im_end|>",
|
349 |
+
"<|im_start|>",
|
350 |
+
"<img>",
|
351 |
+
"</img>",
|
352 |
+
"<IMG_CONTEXT>",
|
353 |
+
"<quad>",
|
354 |
+
"</quad>",
|
355 |
+
"<ref>",
|
356 |
+
"</ref>",
|
357 |
+
"<box>",
|
358 |
+
"</box>",
|
359 |
+
"[PAD]",
|
360 |
+
"<image>",
|
361 |
+
"<im_patch>",
|
362 |
+
"<region>",
|
363 |
+
"<reg>",
|
364 |
+
"</reg>",
|
365 |
+
"<det>",
|
366 |
+
"</det>",
|
367 |
+
"<grd>",
|
368 |
+
"</grd>",
|
369 |
+
"[DET]",
|
370 |
+
"[GRD]",
|
371 |
+
"[SEG]",
|
372 |
+
"[POSE]",
|
373 |
+
"[GEN]",
|
374 |
+
"[EDIT]",
|
375 |
+
"[EMB]",
|
376 |
+
"[EMB2]",
|
377 |
+
"[EMB3]",
|
378 |
+
"[EMB4]",
|
379 |
+
"[EMB5]",
|
380 |
+
"[EMB6]",
|
381 |
+
"[EMB7]",
|
382 |
+
"[EMB8]"
|
383 |
+
],
|
384 |
+
"auto_map": {
|
385 |
+
"AutoTokenizer": [
|
386 |
+
"tokenization_internlm2.InternLM2Tokenizer",
|
387 |
+
null
|
388 |
+
]
|
389 |
+
},
|
390 |
+
"bos_token": "<s>",
|
391 |
+
"chat_template": "{{ bos_token }}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
|
392 |
+
"clean_up_tokenization_spaces": false,
|
393 |
+
"eos_token": "</s>",
|
394 |
+
"model_max_length": 4096,
|
395 |
+
"pad_token": "<unk>",
|
396 |
+
"padding_side": "right",
|
397 |
+
"tokenizer_class": "InternLM2Tokenizer",
|
398 |
+
"tokenizer_file": null,
|
399 |
+
"unk_token": "<unk>"
|
400 |
+
}
|