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* add eli5 examples * add dense query script * query_di * merging * merging * add_utils * adds nearest neighbor wikipedia * batch queries * training_retriever * new notebooks * moved retriever traiing script * finished wiki40b * max_len_fix * train_s2s * retriever_batch_checkpointing * cleanup * merge * dim_fix * fix_indexer * fix_wiki40b_snippets * fix_embed_for_r * fp32 index * fix_sparse_q * joint_training * remove obsolete datasets * add_passage_nn_results * add_passage_nn_results * add_batch_nn * add_batch_nn * add_data_scripts * notebook * notebook * notebook * fix_multi_gpu * add_app * full_caching * full_caching * notebook * sparse_done * images * notebook * add_image_gif * with_Gif * add_contr_image * notebook * notebook * notebook * train_functions * notebook * min_retrieval_length * pandas_option * notebook * min_retrieval_length * notebook * notebook * eval_Retriever * notebook * images * notebook * add_example * add_example * notebook * fireworks * notebook * notebook * joe's notebook comments * app_update * notebook * notebook_link * captions * notebook * assing RetriBert model * add RetriBert to Auto * change AutoLMHead to AutoSeq2Seq * notebook downloads from hf models * style_black * style_black * app_update * app_update * fix_app_update * style * style * isort * Delete WikiELI5training.ipynb * Delete evaluate_eli5.py * Delete WikiELI5explore.ipynb * Delete ExploreWikiELI5Support.html * Delete explainlikeimfive.py * Delete wiki_snippets.py * children before parent * children before parent * style_black * style_black_only * isort * isort_new * Update src/transformers/modeling_retribert.py Co-authored-by: Julien Chaumond <chaumond@gmail.com> * typo fixes * app_without_asset * cleanup * Delete ELI5animation.gif * Delete ELI5contrastive.svg * Delete ELI5wiki_index.svg * Delete choco_bis.svg * Delete fireworks.gif * Delete huggingface_logo.jpg * Delete huggingface_logo.svg * Delete Long_Form_Question_Answering_with_ELI5_and_Wikipedia.ipynb * Delete eli5_app.py * Delete eli5_utils.py * readme * Update README.md * unused imports * moved_info * default_beam * ftuned model * disclaimer * Update src/transformers/modeling_retribert.py Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * black * add_doc * names * isort_Examples * isort_Examples * Add doc to index Co-authored-by: Julien Chaumond <chaumond@gmail.com> Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
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ReStructuredText
40 lines
1014 B
ReStructuredText
RetriBERT
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----------------------------------------------------
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Overview
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~~~~~~~~~~~~~~~~~~~~~
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The RetriBERT model was proposed in the blog post
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`Explain Anything Like I'm Five: A Model for Open Domain Long Form Question Answering <https://yjernite.github.io/lfqa.html>`__,
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RetriBERT is a small model that uses either a single or pair of Bert encoders with lower-dimension projection for dense semantic indexing of text.
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Code to train and use the model can be found `here <https://github.com/huggingface/transformers/tree/master/examples/distillation>`_.
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RetriBertConfig
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.RetriBertConfig
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:members:
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RetriBertTokenizer
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.RetriBertTokenizer
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:members:
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RetriBertTokenizerFast
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.RetriBertTokenizerFast
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:members:
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RetriBertModel
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. autoclass:: transformers.RetriBertModel
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:members:
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