Uploads mt5 for custom testing on korean dataset

added_tokens.json

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+{"COND_LEXICAL_DIV_30": 250105, "COND_SYNTACTIC_DIV_10": 250132, "COND_LEXICAL_DIV_20": 250103, "COND_SEMANTIC_SIM_75": 250126, "COND_SEMANTIC_SIM_85": 250128, "COND_SYNTACTIC_DIV_70": 250145, "COND_LEXICAL_DIV_10": 250101, "COND_LEXICAL_DIV_55": 250111, "COND_SYNTACTIC_DIV_20": 250134, "COND_SEMANTIC_SIM_60": 250123, "COND_LEXICAL_DIV_40": 250107, "COND_SEMANTIC_SIM_50": 250121, "COND_SYNTACTIC_DIV_25": 250135, "COND_SEMANTIC_SIM_40": 250119, "COND_SYNTACTIC_DIV_15": 250133, "COND_SEMANTIC_SIM_45": 250120, "COND_SEMANTIC_SIM_25": 250116, "COND_SEMANTIC_SIM_95": 250130, "COND_SYNTACTIC_DIV_50": 250141, "COND_SEMANTIC_SIM_15": 250114, "COND_SEMANTIC_SIM_65": 250124, "COND_SYNTACTIC_DIV_5": 250140, "COND_SEMANTIC_SIM_80": 250127, "COND_SEMANTIC_SIM_30": 250117, "COND_LEXICAL_DIV_0": 250100, "COND_LEXICAL_DIV_25": 250104, "COND_SYNTACTIC_DIV_30": 250136, "COND_SEMANTIC_SIM_35": 250118, "COND_SEMANTIC_SIM_90": 250129, "COND_SYNTACTIC_DIV_40": 250138, "COND_LEXICAL_DIV_15": 250102, "COND_SYNTACTIC_DIV_65": 250144, "COND_SYNTACTIC_DIV_0": 250131, "COND_SEMANTIC_SIM_70": 250125, "COND_LEXICAL_DIV_35": 250106, "COND_LEXICAL_DIV_5": 250109, "COND_LEXICAL_DIV_45": 250108, "COND_SEMANTIC_SIM_55": 250122, "COND_SYNTACTIC_DIV_45": 250139, "COND_SYNTACTIC_DIV_35": 250137, "COND_SEMANTIC_SIM_20": 250115, "COND_LEXICAL_DIV_60": 250112, "COND_SYNTACTIC_DIV_60": 250143, "COND_SEMANTIC_SIM_10": 250113, "COND_LEXICAL_DIV_50": 250110, "COND_SYNTACTIC_DIV_55": 250142}

config.json

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+{
+  "_name_or_path": "google/mt5-base",
+  "architectures": [
+    "MT5ForConditionalGeneration"
+  ],
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 768,
+  "decoder_start_token_id": 0,
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "mt5",
+  "num_decoder_layers": 12,
+  "num_heads": 12,
+  "num_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_num_buckets": 32,
+  "tie_word_embeddings": false,
+  "tokenizer_class": "T5Tokenizer",
+  "transformers_version": "4.6.1",
+  "use_cache": true,
+  "vocab_size": 250146
+}

pytorch_model.bin

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+size 2329911477

special_tokens_map.json

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+{"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>", "additional_special_tokens": ["COND_LEXICAL_DIV_0", "COND_LEXICAL_DIV_10", "COND_LEXICAL_DIV_15", "COND_LEXICAL_DIV_20", "COND_LEXICAL_DIV_25", "COND_LEXICAL_DIV_30", "COND_LEXICAL_DIV_35", "COND_LEXICAL_DIV_40", "COND_LEXICAL_DIV_45", "COND_LEXICAL_DIV_5", "COND_LEXICAL_DIV_50", "COND_LEXICAL_DIV_55", "COND_LEXICAL_DIV_60", "COND_SEMANTIC_SIM_10", "COND_SEMANTIC_SIM_15", "COND_SEMANTIC_SIM_20", "COND_SEMANTIC_SIM_25", "COND_SEMANTIC_SIM_30", "COND_SEMANTIC_SIM_35", "COND_SEMANTIC_SIM_40", "COND_SEMANTIC_SIM_45", "COND_SEMANTIC_SIM_50", "COND_SEMANTIC_SIM_55", "COND_SEMANTIC_SIM_60", "COND_SEMANTIC_SIM_65", "COND_SEMANTIC_SIM_70", "COND_SEMANTIC_SIM_75", "COND_SEMANTIC_SIM_80", "COND_SEMANTIC_SIM_85", "COND_SEMANTIC_SIM_90", "COND_SEMANTIC_SIM_95", "COND_SYNTACTIC_DIV_0", "COND_SYNTACTIC_DIV_10", "COND_SYNTACTIC_DIV_15", "COND_SYNTACTIC_DIV_20", "COND_SYNTACTIC_DIV_25", "COND_SYNTACTIC_DIV_30", "COND_SYNTACTIC_DIV_35", "COND_SYNTACTIC_DIV_40", "COND_SYNTACTIC_DIV_45", "COND_SYNTACTIC_DIV_5", "COND_SYNTACTIC_DIV_50", "COND_SYNTACTIC_DIV_55", "COND_SYNTACTIC_DIV_60", "COND_SYNTACTIC_DIV_65", "COND_SYNTACTIC_DIV_70"]}

spiece.model

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+size 4309802

tokenizer_config.json

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+{"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>", "extra_ids": 0, "additional_special_tokens": ["COND_LEXICAL_DIV_0", "COND_LEXICAL_DIV_10", "COND_LEXICAL_DIV_15", "COND_LEXICAL_DIV_20", "COND_LEXICAL_DIV_25", "COND_LEXICAL_DIV_30", "COND_LEXICAL_DIV_35", "COND_LEXICAL_DIV_40", "COND_LEXICAL_DIV_45", "COND_LEXICAL_DIV_5", "COND_LEXICAL_DIV_50", "COND_LEXICAL_DIV_55", "COND_LEXICAL_DIV_60", "COND_SEMANTIC_SIM_10", "COND_SEMANTIC_SIM_15", "COND_SEMANTIC_SIM_20", "COND_SEMANTIC_SIM_25", "COND_SEMANTIC_SIM_30", "COND_SEMANTIC_SIM_35", "COND_SEMANTIC_SIM_40", "COND_SEMANTIC_SIM_45", "COND_SEMANTIC_SIM_50", "COND_SEMANTIC_SIM_55", "COND_SEMANTIC_SIM_60", "COND_SEMANTIC_SIM_65", "COND_SEMANTIC_SIM_70", "COND_SEMANTIC_SIM_75", "COND_SEMANTIC_SIM_80", "COND_SEMANTIC_SIM_85", "COND_SEMANTIC_SIM_90", "COND_SEMANTIC_SIM_95", "COND_SYNTACTIC_DIV_0", "COND_SYNTACTIC_DIV_10", "COND_SYNTACTIC_DIV_15", "COND_SYNTACTIC_DIV_20", "COND_SYNTACTIC_DIV_25", "COND_SYNTACTIC_DIV_30", "COND_SYNTACTIC_DIV_35", "COND_SYNTACTIC_DIV_40", "COND_SYNTACTIC_DIV_45", "COND_SYNTACTIC_DIV_5", "COND_SYNTACTIC_DIV_50", "COND_SYNTACTIC_DIV_55", "COND_SYNTACTIC_DIV_60", "COND_SYNTACTIC_DIV_65", "COND_SYNTACTIC_DIV_70"], "special_tokens_map_file": "/home/patrick/.cache/torch/transformers/685ac0ca8568ec593a48b61b0a3c272beee9bc194a3c7241d15dcadb5f875e53.f76030f3ec1b96a8199b2593390c610e76ca8028ef3d24680000619ffb646276", "name_or_path": "google/mt5-base"}