bogdankostic
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Add model files
Browse files- README.md +19 -0
- config.json +62 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
README.md
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---
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language: en
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tags:
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- tapas
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license: apache-2.0
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---
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This model contains the converted PyTorch checkpoint of the original Tensorflow model available in the [TaPas repository](https://github.com/google-research/tapas/blob/master/DENSE_TABLE_RETRIEVER.md#reader-models).
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It is described in Herzig et al.'s (2021) [paper](https://aclanthology.org/2021.naacl-main.43/) _Open Domain Question Answering over Tables via Dense Retrieval_.
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# Usage
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## In Haystack
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If you want to use this model for question-answering over tables, you can load it in [Haystack](https://github.com/deepset-ai/haystack/):
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```python
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from haystack.nodes import TableReader
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table_reader = TableReader(model_name_or_path="deepset/tapas-large-nq-reader")
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```
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config.json
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{
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"aggregation_labels": null,
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"aggregation_loss_weight": 1.0,
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"aggregation_temperature": 1.0,
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"allow_empty_column_selection": false,
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"answer_loss_cutoff": null,
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"answer_loss_importance": 1.0,
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"architectures": [
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"TapasForScoredQA"
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],
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"attention_probs_dropout_prob": 0.034,
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"average_approximation_function": "ratio",
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"average_logits_per_cell": false,
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"cell_selection_preference": null,
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"disable_per_token_loss": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.2,
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"hidden_size": 1024,
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"huber_loss_delta": null,
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"init_cell_selection_weights_to_zero": false,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"layer_norm_eps": 1e-12,
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"max_num_columns": 32,
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"max_num_rows": 64,
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"max_position_embeddings": 1024,
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"model_type": "tapas",
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"no_aggregation_label_index": null,
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"num_aggregation_labels": 0,
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"pad_token_id": 0,
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"positive_label_weight": 10.0,
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"reset_position_index_per_cell": true,
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"select_one_column": true,
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"softmax_temperature": 1.0,
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"torch_dtype": "float32",
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"transformers_version": "4.16.0.dev0",
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"type_vocab_size": [
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3,
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256,
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256,
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2,
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256,
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256,
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10
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],
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"type_vocab_sizes": [
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3,
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256,
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256,
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2,
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256,
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256,
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10
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],
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"use_answer_as_supervision": null,
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"use_gumbel_for_aggregation": false,
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"use_gumbel_for_cells": false,
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"use_normalized_answer_loss": false,
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"vocab_size": 30522
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:4267f2a38e29c2e2e9fadef32ab4a70a81a07ffeaf9b554dfa1d2ce2615ccee6
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size 1347084063
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special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "additional_special_tokens": ["[EMPTY]"]}
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tokenizer_config.json
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{"do_lower_case": true, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "empty_token": "[EMPTY]", "tokenize_chinese_chars": true, "strip_accents": null, "cell_trim_length": -1, "max_column_id": null, "max_row_id": null, "strip_column_names": false, "update_answer_coordinates": false, "min_question_length": null, "max_question_length": null, "model_max_length": 512, "additional_special_tokens": ["[EMPTY]"], "tokenizer_class": "TapasTokenizer"}
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vocab.txt
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