Raphael Sourty
commited on
initialize model
Browse files- README.md +137 -0
- config.json +25 -0
- linear.pt +3 -0
- metadata.json +1 -0
- model.safetensors +3 -0
- special_tokens_map.json +45 -0
- tokenizer.json +0 -0
- tokenizer_config.json +73 -0
- vocab.txt +0 -0
README.md
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---
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license: mit
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---
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---
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language:
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- en
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license: mit
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---
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This model was trained with [Neural-Cherche](https://github.com/raphaelsty/neural-cerche). You can find details on how to fine-tune it in the [Neural-Cherche](https://github.com/raphaelsty/neural-cherche) repository.
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This model is an `all-mpnet-base-v2` as a ColBERT.
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```sh
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pip install neural-cherche
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```
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## Retriever
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```python
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from neural_cherche import models, retrieve
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import torch
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device = "cuda" if torch.cuda.is_available() else "cpu"
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batch_size = 32
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documents = [
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{"id": 0, "document": "Food"},
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{"id": 1, "document": "Sports"},
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{"id": 2, "document": "Cinema"},
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]
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queries = ["Food", "Sports", "Cinema"]
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model = models.ColBERT(
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model_name_or_path="raphaelsty",
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device=device,
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)
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retriever = retrieve.ColBERT(
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key="id",
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on=["document"],
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model=model,
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)
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documents_embeddings = retriever.encode_documents(
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documents=documents,
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batch_size=batch_size,
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)
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retriever = retriever.add(
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documents_embeddings=documents_embeddings,
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)
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queries_embeddings = retriever.encode_queries(
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queries=queries,
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batch_size=batch_size,
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)
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scores = retriever(
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queries_embeddings=queries_embeddings,
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batch_size=batch_size,
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k=3,
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)
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scores
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```
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## Ranker
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```python
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from neural_cherche import models, rank, retrieve
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import torch
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device = "cuda" if torch.cuda.is_available() else "cpu"
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batch_size = 32
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documents = [
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{"id": "doc1", "title": "Paris", "text": "Paris is the capital of France."},
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{"id": "doc2", "title": "Montreal", "text": "Montreal is the largest city in Quebec."},
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{"id": "doc3", "title": "Bordeaux", "text": "Bordeaux in Southwestern France."},
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]
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queries = [
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"What is the capital of France?",
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"What is the largest city in Quebec?",
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"Where is Bordeaux?",
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]
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retriever = retrieve.TfIdf(
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key="id",
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on=["title", "text"],
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)
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model = models.ColBERT(
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model_name_or_path="sentence-transformers/all-mpnet-base-v2",
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device=device,
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)
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ranker = rank.ColBERT(
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key="id",
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on=["title", "text"],
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model=model
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)
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retriever_documents_embeddings = retriever.encode_documents(
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documents=documents,
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)
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retriever.add(
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documents_embeddings=retriever_documents_embeddings,
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)
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ranker_documents_embeddings = ranker.encode_documents(
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documents=documents,
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batch_size=batch_size,
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)
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retriever_queries_embeddings = retriever.encode_queries(
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queries=queries,
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)
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ranker_queries_embeddings = ranker.encode_queries(
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queries=queries,
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batch_size=batch_size,
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)
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candidates = retriever(
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queries_embeddings=retriever_queries_embeddings,
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k=1000,
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)
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scores = ranker(
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documents=candidates,
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queries_embeddings=ranker_queries_embeddings,
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documents_embeddings=ranker_documents_embeddings,
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k=100,
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batch_size=32,
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)
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scores
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```
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config.json
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{
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"_name_or_path": "sentence-transformers/all-mpnet-base-v2",
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"architectures": [
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"MPNetForMaskedLM"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"eos_token_id": 2,
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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-05,
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"max_position_embeddings": 514,
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"model_type": "mpnet",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"output_hidden_states": true,
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"pad_token_id": 1,
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"relative_attention_num_buckets": 32,
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"torch_dtype": "float32",
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"transformers_version": "4.35.2",
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"vocab_size": 30527
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}
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linear.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:51c6fe3495544322ca5339d03f91afe54f6234d441f5b69b6f062f483fc9ce99
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size 394391
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metadata.json
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{"max_length_query": 32, "max_length_document": 256, "query_prefix": "[Q] ", "document_prefix": "[D] "}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:987c71696a5e133e2dad24165c4839b9cf7cf1744e30cfe4eb3a2fcd077cf4eb
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size 438097372
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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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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"cls_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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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": true,
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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": "<pad>",
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"sep_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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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": "<s>",
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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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"1": {
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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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"2": {
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"content": "</s>",
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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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"3": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": true,
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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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"104": {
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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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"30526": {
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"content": "<mask>",
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"lstrip": true,
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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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"bos_token": "<s>",
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"clean_up_tokenization_spaces": true,
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"cls_token": "<s>",
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"device": "cuda",
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"do_lower_case": true,
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"eos_token": "</s>",
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"mask_token": "<mask>",
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"max_length": 128,
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"model_max_length": 512,
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"pad_to_multiple_of": null,
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"pad_token": "<pad>",
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"pad_token_type_id": 0,
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"padding_side": "right",
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"sep_token": "</s>",
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"stride": 0,
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "MPNetTokenizer",
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"truncation_side": "right",
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"truncation_strategy": "longest_first",
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"unk_token": "[UNK]"
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}
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vocab.txt
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