ZjHpSrSSKJr SSKJr SSKJr SSKJr \"SS 9\"S S \555r S /r g ) zRAG model configuration)strict)PreTrainedConfig)auto_docstring) AutoConfig) checkpointc^\rSrSr%SrSrSrSr\S-\ S'Sr \ \ S'Sr \ S-\ S'Sr\S-\ S 'Sr\S-\ S 'Sr\\\-S-\ S 'Sr\S-\ S 'S r\ \ S'Sr\ \ S'Sr\\ S'Sr\\ S'Sr\\ S'Sr\\ S'Sr\ \ S'Sr\ \ S'Sr\ \ S'Sr\ S-\ S'Sr\ S-\ S 'S!r\ \ S"'S!r\ \ S#'S$r \!\ S%'Sr"\ \ S&'S!r#\ \ S''S!r$\ \ S('S!r%\ \ S)'Sr&\ \ S*'Sr'\ S-\ S+'U4S,jr(\)S-\*S.\*S/\*4S0j5r+S1r,U=r-$)2 RagConfiga] prefix (`str`, *optional*): A string prefix prepended to every input before passing to the generator model. title_sep (`str`, *optional*, defaults to `" / "`): Separator inserted between the title and the text of the retrieved document when calling [`RagRetriever`]. doc_sep (`str`, *optional*, defaults to `" // "`): Separator inserted between the text of the retrieved document and the original input when calling [`RagRetriever`]. n_docs (`int`, *optional*, defaults to 5): Number of documents to retrieve. max_combined_length (`int`, *optional*, defaults to 300): Max length of contextualized input returned by [`~RagRetriever.__call__`]. retrieval_vector_size (`int`, *optional*, defaults to 768): Dimensionality of the document embeddings indexed by [`RagRetriever`]. retrieval_batch_size (`int`, *optional*, defaults to 8): Retrieval batch size, defined as the number of queries issues concurrently to the faiss index encapsulated [`RagRetriever`]. dataset (`str`, *optional*, defaults to `"wiki_dpr"`): A dataset identifier of the indexed dataset in HuggingFace Datasets (list all available datasets and ids using `datasets.list_datasets()`). dataset_split (`str`, *optional*, defaults to `"train"`): Which split of the `dataset` to load. index_name (`str`, *optional*, defaults to `"compressed"`): The index name of the index associated with the `dataset`. One can choose between `"legacy"`, `"exact"` and `"compressed"`. index_path (`str`, *optional*): The path to the serialized faiss index on disk. passages_path (`str`, *optional*): A path to text passages compatible with the faiss index. Required if using [`~models.rag.retrieval_rag.LegacyIndex`] use_dummy_dataset (`bool`, *optional*, defaults to `False`): Whether to load a "dummy" variant of the dataset specified by `dataset`. reduce_loss (`bool`, *optional*, defaults to `False`): Whether or not to reduce the NLL loss using the `torch.Tensor.sum` operation. label_smoothing (`float`, *optional*, defaults to 0.0): Only relevant if `return_loss` is set to `True`. Controls the `epsilon` parameter value for label smoothing in the loss calculation. If set to 0, no label smoothing is performed. do_deduplication (`bool`, *optional*, defaults to `True`): Whether or not to deduplicate the generations from different context documents for a given input. Has to be set to `False` if used while training with distributed backend. exclude_bos_score (`bool`, *optional*, defaults to `False`): Whether or not to disregard the BOS token when computing the loss. do_marginalize (`bool`, *optional*, defaults to `False`): If `True`, the logits are marginalized over all documents by making use of `torch.nn.functional.log_softmax`. output_retrieved (`bool`, *optional*, defaults to `False`): If set to `True`, `retrieved_doc_embeds`, `retrieved_doc_ids`, `context_input_ids` and `context_attention_mask` are returned. See returned tensors for more detail. dataset_revision (`str`, *optional*,): The revision (commit hash, tag, or branch) of the Hugging Face dataset used for retrieval. ragTN vocab_sizeis_encoder_decoderprefix bos_token_id pad_token_id eos_token_iddecoder_start_token_idz / title_sepz // doc_sepn_docsi,max_combined_lengthiretrieval_vector_sizeretrieval_batch_sizewiki_dprdatasettrain dataset_split compressed index_name index_path passages_pathFuse_dummy_dataset reduce_lossglabel_smoothingdo_deduplicationexclude_bos_scoredo_marginalizeoutput_retrieved use_cachedataset_revisionc l>SU;dSU;a[SURSU35eURS5nURS5nURS5nURS5n[R"U40UD6Ul[R"U40UD6Ul[TU] "S0UD6 g)Nquestion_encoder generatorzA configuration of type zt cannot be instantiated because not both `question_encoder` and `generator` sub-configurations are passed, but only model_type) ValueErrorr2popr for_modelr0r1super __post_init__)selfkwargsquestion_encoder_configquestion_encoder_model_typedecoder_configdecoder_model_type __class__s z/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/rag/configuration_rag.pyr8RagConfig.__post_init__ms V +{&/H*4??*;r^sO.3#02pw pwpwf -rB