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Browse files- artifact.metadata +60 -0
- config.json +26 -0
- model.safetensors +3 -0
- special_tokens_map.json +37 -0
- tokenizer.json +0 -0
- tokenizer_config.json +55 -0
- vocab.txt +0 -0
artifact.metadata
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{
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"query_token_id": "[unused0]",
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"doc_token_id": "[unused1]",
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"query_token": "[Q]",
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"doc_token": "[D]",
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"ncells": null,
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"centroid_score_threshold": null,
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"ndocs": null,
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"load_index_with_mmap": false,
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"index_path": null,
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"index_bsize": 64,
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"nbits": 4,
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"kmeans_niters": 20,
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"resume": false,
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"pool_factor": 1,
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"clustering_mode": "hierarchical",
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"protected_tokens": 0,
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"similarity": "cosine",
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"bsize": 32,
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"accumsteps": 1,
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"lr": 5e-6,
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"maxsteps": 3000,
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"save_every": 9,
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"warmup": 9,
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"warmup_bert": null,
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"relu": false,
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"nway": 2,
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"use_ib_negatives": true,
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"reranker": false,
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"distillation_alpha": 1.0,
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"ignore_scores": false,
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"model_name": "chunks_colbert_v2",
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"query_maxlen": 32,
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"attend_to_mask_tokens": false,
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"interaction": "colbert",
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"dim": 128,
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"doc_maxlen": 256,
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"mask_punctuation": true,
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"checkpoint": "colbert-ir\/colbertv2.0",
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"triples": "\/kaggle\/working\/train\/triples.train.colbert.jsonl",
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"collection": "\/kaggle\/working\/train\/corpus.train.colbert.tsv",
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"queries": "\/kaggle\/working\/train\/queries.train.colbert.tsv",
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"index_name": null,
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"overwrite": false,
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"root": ".ragatouille\/",
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"experiment": "colbert",
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"index_root": null,
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"name": "2024-09\/26\/13.47.00",
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"rank": 0,
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"nranks": 2,
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"amp": true,
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"gpus": 2,
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"avoid_fork_if_possible": false,
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"meta": {
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"hostname": "b068ccaf4413",
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"current_datetime": "Sep 26, 2024 ; 1:51PM UTC (+0000)",
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"cmd": "\/opt\/conda\/lib\/python3.10\/site-packages\/ipykernel_launcher.py -f \/root\/.local\/share\/jupyter\/runtime\/kernel-978a078a-bdab-4460-867f-f9b8ef96e70a.json",
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"version": "colbert-v0.4"
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}
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}
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config.json
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{
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"_name_or_path": "colbert-ir/colbertv2.0",
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"architectures": [
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"HF_ColBERT"
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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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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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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": 12,
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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": "4.39.3",
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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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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:512908ef161263c44916557e4afe667f8bada9a30a5dc2bb54f35804dcaa4e01
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size 438345624
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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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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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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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"unk_token": "[UNK]"
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}
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vocab.txt
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