abinesh03 commited on
Commit
a21a018
1 Parent(s): 6f21f1a

Update spaCy pipeline

Browse files
.gitattributes CHANGED
@@ -32,3 +32,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ en_pipeline-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
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+ transformer/model filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,56 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ tags:
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+ - spacy
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+ - token-classification
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+ language:
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+ - en
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+ model-index:
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+ - name: en_pipeline
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+ results:
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+ - task:
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+ name: NER
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+ type: token-classification
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+ metrics:
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+ - name: NER Precision
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+ type: precision
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+ value: 1.0
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+ - name: NER Recall
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+ type: recall
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+ value: 1.0
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+ - name: NER F Score
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+ type: f_score
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+ value: 1.0
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+ ---
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+ | Feature | Description |
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+ | --- | --- |
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+ | **Name** | `en_pipeline` |
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+ | **Version** | `0.0.0` |
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+ | **spaCy** | `>=3.5.1,<3.6.0` |
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+ | **Default Pipeline** | `transformer`, `ner` |
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+ | **Components** | `transformer`, `ner` |
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+ | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
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+ | **Sources** | n/a |
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+ | **License** | n/a |
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+ | **Author** | [n/a]() |
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+
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+ ### Label Scheme
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+
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+ <details>
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+
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+ <summary>View label scheme (5 labels for 1 components)</summary>
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+
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+ | Component | Labels |
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+ | --- | --- |
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+ | **`ner`** | `avg rating`, `name`, `price`, `quantity`, `total rating` |
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+
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+ </details>
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+
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+ ### Accuracy
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+
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+ | Type | Score |
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+ | --- | --- |
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+ | `ENTS_F` | 100.00 |
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+ | `ENTS_P` | 100.00 |
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+ | `ENTS_R` | 100.00 |
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+ | `TRANSFORMER_LOSS` | 1.73 |
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+ | `NER_LOSS` | 1.25 |
config.cfg ADDED
@@ -0,0 +1,146 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ [paths]
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+ train = "corpus/train.spacy"
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+ dev = "corpus/test.spacy"
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+ vectors = null
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+ init_tok2vec = null
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+
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+ [system]
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+ gpu_allocator = "pytorch"
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+ seed = 0
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+
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+ [nlp]
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+ lang = "en"
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+ pipeline = ["transformer","ner"]
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+ batch_size = 128
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+ disabled = []
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+ before_creation = null
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+ after_creation = null
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+ after_pipeline_creation = null
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+ tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
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+
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+ [components]
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+
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+ [components.ner]
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+ factory = "ner"
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+ incorrect_spans_key = null
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+ moves = null
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+ scorer = {"@scorers":"spacy.ner_scorer.v1"}
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+ update_with_oracle_cut_size = 100
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+
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+ [components.ner.model]
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+ @architectures = "spacy.TransitionBasedParser.v2"
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+ state_type = "ner"
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+ extra_state_tokens = false
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+ hidden_width = 64
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+ maxout_pieces = 2
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+ use_upper = false
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+ nO = null
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+
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+ [components.ner.model.tok2vec]
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+ @architectures = "spacy-transformers.TransformerListener.v1"
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+ grad_factor = 1.0
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+ pooling = {"@layers":"reduce_mean.v1"}
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+ upstream = "*"
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+
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+ [components.transformer]
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+ factory = "transformer"
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+ max_batch_items = 4096
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+ set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
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+
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+ [components.transformer.model]
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+ @architectures = "spacy-transformers.TransformerModel.v3"
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+ name = "roberta-base"
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+ mixed_precision = false
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+
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+ [components.transformer.model.get_spans]
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+ @span_getters = "spacy-transformers.strided_spans.v1"
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+ window = 128
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+ stride = 96
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+
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+ [components.transformer.model.grad_scaler_config]
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+
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+ [components.transformer.model.tokenizer_config]
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+ use_fast = true
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+
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+ [components.transformer.model.transformer_config]
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+
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+ [corpora]
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+
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+ [corpora.dev]
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+ @readers = "spacy.Corpus.v1"
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+ path = ${paths.dev}
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+ max_length = 0
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+ gold_preproc = false
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+ limit = 0
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+ augmenter = null
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+
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+ [corpora.train]
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+ @readers = "spacy.Corpus.v1"
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+ path = ${paths.train}
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+ max_length = 0
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+ gold_preproc = false
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+ limit = 0
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+ augmenter = null
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+
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+ [training]
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+ accumulate_gradient = 3
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+ dev_corpus = "corpora.dev"
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+ train_corpus = "corpora.train"
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+ seed = ${system.seed}
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+ gpu_allocator = ${system.gpu_allocator}
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+ dropout = 0.1
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+ patience = 1600
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+ max_epochs = 0
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+ max_steps = 20000
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+ eval_frequency = 200
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+ frozen_components = []
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+ annotating_components = []
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+ before_to_disk = null
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+ before_update = null
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+
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+ [training.batcher]
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+ @batchers = "spacy.batch_by_padded.v1"
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+ discard_oversize = true
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+ size = 1000
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+ buffer = 256
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+ get_length = null
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+
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+ [training.logger]
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+ @loggers = "spacy.ConsoleLogger.v1"
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+ progress_bar = false
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+
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+ [training.optimizer]
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+ @optimizers = "Adam.v1"
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+ beta1 = 0.9
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+ beta2 = 0.999
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+ L2_is_weight_decay = true
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+ L2 = 0.01
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+ grad_clip = 1.0
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+ use_averages = false
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+ eps = 0.00000001
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+
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+ [training.optimizer.learn_rate]
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+ @schedules = "warmup_linear.v1"
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+ warmup_steps = 250
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+ total_steps = 2000
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+ initial_rate = 0.00005
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+
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+ [training.score_weights]
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+ ents_f = 1.0
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+ ents_p = 0.0
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+ ents_r = 0.0
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+ ents_per_type = null
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+
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+ [pretraining]
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+
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+ [initialize]
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+ vectors = ${paths.vectors}
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+ init_tok2vec = ${paths.init_tok2vec}
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+ vocab_data = null
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+ lookups = null
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+ before_init = null
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+ after_init = null
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+
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+ [initialize.components]
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+
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+ [initialize.tokenizer]
en_pipeline-any-py3-none-any.whl ADDED
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meta.json ADDED
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+ {
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+ "lang":"en",
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+ "name":"pipeline",
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+ "version":"0.0.0",
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+ "description":"",
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+ "author":"",
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+ "email":"",
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+ "url":"",
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+ "license":"",
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+ "spacy_version":">=3.5.1,<3.6.0",
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+ "spacy_git_version":"Unknown",
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+ },
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+ "labels":{
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+ "transformer":[
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+
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+ ],
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+ "ner":[
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+ "avg rating",
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+ "name",
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+ "price",
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+ "quantity",
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+ "total rating"
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+ ]
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+ },
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+ "pipeline":[
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+ "transformer",
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+ "ner"
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+ ],
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+ "components":[
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+ "transformer",
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+ "ner"
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+ ],
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+ "disabled":[
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+ ],
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+ "performance":{
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+ "ents_per_type":{
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+ "name":{
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+ },
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+ "quantity":{
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+ "p":1.0,
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+ "r":1.0,
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+ "f":1.0
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+ },
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+ "avg rating":{
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+ "p":1.0,
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+ "r":1.0,
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+ "f":1.0
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+ },
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+ "total rating":{
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+ "p":1.0,
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+ "r":1.0,
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+ "f":1.0
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+ }
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+ },
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+ "transformer_loss":0.0173356068,
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+ "ner_loss":0.0124846729
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+ },
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+ "requirements":[
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+ "spacy-transformers>=1.2.2,<1.3.0"
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+ ]
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+ }
ner/cfg ADDED
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+ {
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+ "moves":null,
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+ "update_with_oracle_cut_size":100,
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+ "multitasks":[
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+
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+ ],
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+ "min_action_freq":1,
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+ "learn_tokens":false,
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+ "beam_width":1,
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+ "beam_density":0.0,
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+ "beam_update_prob":0.0,
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+ "incorrect_spans_key":null
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+ }
ner/model ADDED
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854
+ "Nev.",
855
+ "Nevada",
856
+ "New Hampshire",
857
+ "New Jersey",
858
+ "New Mexico",
859
+ "New York",
860
+ "North Carolina",
861
+ "North Dakota",
862
+ "Not",
863
+ "Nothin",
864
+ "Nothin'",
865
+ "Nothin\u2019",
866
+ "Nov",
867
+ "Nov.",
868
+ "November",
869
+ "Nuggets",
870
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871
+ "Nuthin'",
872
+ "Nuthin\u2019",
873
+ "O",
874
+ "O'clock",
875
+ "O.O",
876
+ "O.o",
877
+ "OSK",
878
+ "O_O",
879
+ "O_o",
880
+ "Oct",
881
+ "Oct.",
882
+ "October",
883
+ "Off",
884
+ "Okla",
885
+ "Okla.",
886
+ "Oklahoma",
887
+ "Ol",
888
+ "Ol'",
889
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890
+ "Omega",
891
+ "Onions",
892
+ "Ore",
893
+ "Ore.",
894
+ "Oregon",
895
+ "Origin",
896
+ "Original",
897
+ "Ought",
898
+ "O\u2019clock",
899
+ "P",
900
+ "PWPCoca",
901
+ "Pa",
902
+ "Pa.",
903
+ "Pasar",
904
+ "PediaSure",
905
+ "Pennsylvania",
906
+ "Ph",
907
+ "Ph.D.",
908
+ "Pork",
909
+ "Potato",
910
+ "Powder",
911
+ "Prego",
912
+ "Premium",
913
+ "Prepacked",
914
+ "Prima",
915
+ "Prof",
916
+ "Prof.",
917
+ "Professional",
918
+ "Puffs",
919
+ "Puppies",
920
+ "Purchase",
921
+ "Pure",
922
+ "Q",
923
+ "QT",
924
+ "Quick",
925
+ "R",
926
+ "ROOT",
927
+ "Ready",
928
+ "Refreshing",
929
+ "Regular",
930
+ "Rep",
931
+ "Rep.",
932
+ "Rev",
933
+ "Rev.",
934
+ "Rice",
935
+ "Roll",
936
+ "Rose",
937
+ "Royal",
938
+ "Rust",
939
+ "S",
940
+ "S.C.",
941
+ "Salmon",
942
+ "Satay",
943
+ "Save",
944
+ "Seafood",
945
+ "Sen",
946
+ "Sen.",
947
+ "Seng",
948
+ "Sensitive",
949
+ "Sep",
950
+ "Sep.",
951
+ "Sept",
952
+ "Sept.",
953
+ "September",
954
+ "Serenity",
955
+ "Set",
956
+ "Seventh",
957
+ "Sha",
958
+ "Shampoo",
959
+ "She",
960
+ "She's",
961
+ "Sheba",
962
+ "Sheet",
963
+ "She\u2019s",
964
+ "Should",
965
+ "Silken",
966
+ "Single",
967
+ "Smooth",
968
+ "Somethin",
969
+ "Somethin'",
970
+ "Somethin\u2019",
971
+ "Soothing",
972
+ "South Carolina",
973
+ "Spend",
974
+ "Spicy",
975
+ "St",
976
+ "St.",
977
+ "Stone",
978
+ "Strawberry",
979
+ "Strong",
980
+ "Style",
981
+ "Sugar",
982
+ "Sugar@",
983
+ "Sweet",
984
+ "T",
985
+ "Taste",
986
+ "Tea",
987
+ "Tender",
988
+ "Tenn",
989
+ "Tenn.",
990
+ "Tennessee",
991
+ "Thai",
992
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993
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994
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995
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996
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997
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998
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999
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1000
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1001
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1002
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1003
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1004
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1005
+ "Tiles",
1006
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1007
+ "Tofu",
1008
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1009
+ "TripleSure",
1010
+ "Trout",
1011
+ "Tub",
1012
+ "Tube",
1013
+ "Tuna",
1014
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1015
+ "Umbrella",
1016
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1017
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1018
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1019
+ "V_V",
1020
+ "Va",
1021
+ "Va.",
1022
+ "Vegetables",
1023
+ "Virginia",
1024
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1025
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1026
+ "Wash",
1027
+ "Wash.",
1028
+ "Washington",
1029
+ "Water",
1030
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1031
+ "Weiman",
1032
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1033
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1034
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1035
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1036
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1037
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1038
+ "When's",
1039
+ "When\u2019s",
1040
+ "Where",
1041
+ "Where's",
1042
+ "Where\u2019s",
1043
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1044
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1045
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1046
+ "Who\u2019s",
1047
+ "Why",
1048
+ "Why's",
1049
+ "Why\u2019s",
1050
+ "Win",
1051
+ "Wiper",
1052
+ "Wipes",
1053
+ "Wis",
1054
+ "Wis.",
1055
+ "Wisconsin",
1056
+ "Wo",
1057
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1058
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1059
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1060
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1061
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1062
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1063
+ "X.X.",
1064
+ "X.x",
1065
+ "X.x.",
1066
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1067
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1068
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1069
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1070
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1071
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1072
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1073
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1074
+ "Xx'",
1075
+ "Xx'x",
1076
+ "Xx'xx",
1077
+ "Xx.",
1078
+ "Xx.X.",
1079
+ "XxXxxx",
1080
+ "XxXxxxXxxxx",
1081
+ "XxXxxxx",
1082
+ "Xxx",
1083
+ "Xxx'x",
1084
+ "Xxx.",
1085
+ "Xxxx",
1086
+ "Xxxx'",
1087
+ "Xxxx'x",
1088
+ "Xxxx.",
1089
+ "XxxxXxxxx",
1090
+ "Xxxxx",
1091
+ "Xxxxx'",
1092
+ "Xxxxx'x",
1093
+ "Xxxxx.",
1094
+ "Xxxxx@",
1095
+ "XxxxxXxxx",
1096
+ "Xxxxx\u2019",
1097
+ "Xxxxx\u2019x",
1098
+ "Xxxx\u2019",
1099
+ "Xxxx\u2019x",
1100
+ "Xxx\u2019x",
1101
+ "Xx\u2019",
1102
+ "Xx\u2019x",
1103
+ "Xx\u2019xx",
1104
+ "X\u2019x",
1105
+ "X\u2019xxxx",
1106
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1107
+ "Yoghurt",
1108
+ "You",
1109
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1110
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1111
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1112
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1113
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1114
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1115
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1116
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1117
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1120
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1121
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1122
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1123
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1124
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1125
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1126
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1127
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1128
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1129
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1130
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1131
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1132
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1133
+ "__^",
1134
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1135
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1136
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1137
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1138
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1139
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1140
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1141
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1142
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1143
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1144
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1145
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1146
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1147
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1148
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1149
+ "adm.",
1150
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1151
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1152
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1153
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1154
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1155
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1156
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1157
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1158
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1159
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1160
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1161
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1162
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1163
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1164
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1165
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1166
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1167
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1168
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1169
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1170
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1171
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1172
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1173
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1174
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1175
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1176
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1177
+ "apr.",
1178
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1179
+ "ar@",
1180
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1181
+ "ariz",
1182
+ "ariz.",
1183
+ "ark",
1184
+ "ark.",
1185
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1186
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1187
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1188
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1189
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1190
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1191
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1192
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1193
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1194
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1195
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1196
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1197
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1198
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1199
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1200
+ "b.",
1201
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1202
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1203
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1204
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1205
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1206
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1207
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1208
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1209
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1210
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1211
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1212
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1213
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1214
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1215
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1217
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1218
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1219
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1220
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1221
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1222
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1223
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1224
+ "calif.",
1225
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1226
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1227
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1228
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1229
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1230
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1231
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1232
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1233
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1234
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1235
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1236
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1237
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1238
+ "chamomile",
1239
+ "chef",
1240
+ "chicken",
1241
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1242
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1243
+ "chocolate",
1244
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1245
+ "choon",
1246
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1247
+ "cleaning",
1248
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1249
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1250
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1251
+ "coffee",
1252
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1253
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1254
+ "colo.",
1255
+ "come",
1256
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1257
+ "conn.",
1258
+ "cook",
1259
+ "cookies",
1260
+ "corn",
1261
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1262
+ "corp.",
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1264
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1265
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1266
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1267
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1268
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1269
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1270
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1271
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1274
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1276
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1277
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1278
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1280
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1281
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1282
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1283
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1285
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1286
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1287
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1288
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1289
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1290
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1291
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1292
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1293
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1294
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1296
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1299
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1300
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1301
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1303
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1304
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1305
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1306
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1309
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1310
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1312
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1313
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1315
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1318
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1346
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1349
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1350
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1352
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1354
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1356
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1360
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1363
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1371
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1374
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1381
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1382
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1384
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1386
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1387
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1388
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1389
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1390
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1392
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1393
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1394
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1396
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1397
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1400
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1407
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1410
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1411
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1413
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1421
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1435
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1442
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1456
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1471
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1472
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1474
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1476
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1479
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1487
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1491
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1494
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1496
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1500
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1519
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1521
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1523
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1528
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1530
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1532
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1534
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1620
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1621
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1622
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1623
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1624
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1625
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1626
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1627
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1628
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1629
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1630
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1631
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1632
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1633
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1634
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1635
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1636
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1637
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1638
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1639
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1640
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1641
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1642
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1643
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1644
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1645
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1646
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1647
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1648
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1649
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1650
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1651
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1652
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1653
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1654
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1655
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1656
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1657
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1658
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1659
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1660
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1661
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1662
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1663
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1664
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1665
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1666
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1667
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1668
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1669
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1670
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1671
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1672
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1673
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1674
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1675
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1676
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1677
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1678
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1679
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1680
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1681
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1682
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1683
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1684
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1685
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1686
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1687
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1688
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1689
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1690
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1691
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1692
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1693
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1694
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1695
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1696
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1697
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1698
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1699
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1700
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1701
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1703
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1705
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1706
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1707
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1709
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1710
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1711
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1712
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1713
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1714
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1715
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1716
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1717
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1718
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1719
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1720
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1721
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1722
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1723
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1724
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1725
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1726
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1727
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1728
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1729
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1730
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1731
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1732
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1733
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1734
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1735
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1736
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1737
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1738
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1739
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1740
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1741
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1742
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1743
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1744
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1745
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1746
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1747
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1748
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1749
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1750
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1751
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1752
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1753
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1754
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1755
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1756
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1757
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1758
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1759
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1760
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1761
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1762
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1763
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1764
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1765
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1766
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1767
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1768
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1769
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1770
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1771
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1772
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1773
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1774
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1775
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1776
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1777
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1778
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1779
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1780
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1781
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1782
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1783
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1784
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1785
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1786
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1787
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1788
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1789
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1790
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1791
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1792
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1793
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1794
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1795
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1796
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1797
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1798
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1799
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1800
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1801
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1802
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1803
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1804
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1805
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1806
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1807
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1808
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1809
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1810
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1811
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1812
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1813
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1814
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1815
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1816
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1817
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1818
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1819
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1820
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1821
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1822
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1823
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1824
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1825
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1826
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1827
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1828
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1829
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1830
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1831
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1832
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1833
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1834
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1835
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1836
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1837
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1838
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1839
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1840
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1841
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1842
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1843
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1844
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1845
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1846
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1847
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1848
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1851
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1852
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1853
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1854
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1855
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1856
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1857
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1858
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1859
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1860
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1861
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1862
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1863
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1864
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1865
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1866
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1867
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1868
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1869
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1870
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1872
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1873
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1874
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1875
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1877
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1878
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1879
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1880
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1910
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1912
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1915
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1916
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1919
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1920
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1921
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1922
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1927
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1928
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1929
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1930
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1932
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1942
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1944
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1945
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1946
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1947
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1948
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1949
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1951
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1952
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1953
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1954
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1957
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1961
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1964
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1966
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1970
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1972
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1973
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1974
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1975
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1976
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1977
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1981
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1983
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1985
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1986
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1987
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1988
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1989
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1990
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1991
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1992
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1993
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1994
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1995
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1996
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1997
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1998
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1999
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2000
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2001
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2002
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2003
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2004
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2005
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2006
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2007
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2008
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2009
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2010
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2011
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2012
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2013
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2014
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2015
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2016
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2017
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2018
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2019
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2020
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2021
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2022
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2023
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2024
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2025
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2026
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2027
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2028
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2029
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2030
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2031
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2032
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2033
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2034
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2035
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2036
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2037
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2038
+ "x\ufe35x",
2039
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2040
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2041
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2042
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2043
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2044
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2045
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2046
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2047
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2048
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2049
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2050
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2051
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2052
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2053
+ "zero",
2054
+ "zes",
2055
+ "|",
2056
+ "}",
2057
+ "\u00a0",
2058
+ "\u00ac",
2059
+ "\u00ac_\u00ac",
2060
+ "\u00af",
2061
+ "\u00af\\(x)/\u00af",
2062
+ "\u00af\\(\u30c4)/\u00af",
2063
+ "\u00b0",
2064
+ "\u00b0C.",
2065
+ "\u00b0F.",
2066
+ "\u00b0K.",
2067
+ "\u00b0X.",
2068
+ "\u00b0c.",
2069
+ "\u00b0f.",
2070
+ "\u00b0k.",
2071
+ "\u00b0x.",
2072
+ "\u00e4",
2073
+ "\u00e4.",
2074
+ "\u00f6",
2075
+ "\u00f6.",
2076
+ "\u00fc",
2077
+ "\u00fc.",
2078
+ "\u0ca0",
2079
+ "\u0ca0_\u0ca0",
2080
+ "\u0ca0\ufe35\u0ca0",
2081
+ "\u2014",
2082
+ "\u2018",
2083
+ "\u2018S",
2084
+ "\u2018X",
2085
+ "\u2018s",
2086
+ "\u2018x",
2087
+ "\u2019",
2088
+ "\u2019-(",
2089
+ "\u2019-)",
2090
+ "\u2019Cause",
2091
+ "\u2019Cos",
2092
+ "\u2019Coz",
2093
+ "\u2019Cuz",
2094
+ "\u2019S",
2095
+ "\u2019X",
2096
+ "\u2019Xxx",
2097
+ "\u2019Xxxxx",
2098
+ "\u2019am",
2099
+ "\u2019bout",
2100
+ "\u2019cause",
2101
+ "\u2019cos",
2102
+ "\u2019coz",
2103
+ "\u2019cuz",
2104
+ "\u2019d",
2105
+ "\u2019em",
2106
+ "\u2019ll",
2107
+ "\u2019m",
2108
+ "\u2019nuff",
2109
+ "\u2019re",
2110
+ "\u2019s",
2111
+ "\u2019ve",
2112
+ "\u2019x",
2113
+ "\u2019xx",
2114
+ "\u2019xxx",
2115
+ "\u2019xxxx",
2116
+ "\u2019y",
2117
+ "\u2019\u2019",
2118
+ "\u2022",
2119
+ "\u2022$0.12",
2120
+ "\u2022$0.17",
2121
+ "\u2022$0.19",
2122
+ "\u2022$0.23",
2123
+ "\u2022$0.27",
2124
+ "\u2022$0.29",
2125
+ "\u2022$0.43",
2126
+ "\u2022$0.52",
2127
+ "\u2022$0.54",
2128
+ "\u2022$0.62",
2129
+ "\u2022$0.72",
2130
+ "\u2022$2.27",
2131
+ "\u2022$d.dd",
2132
+ "\u2022Halal",
2133
+ "\u2022Organic",
2134
+ "\u2022Xxxxx",
2135
+ "\u2022halal",
2136
+ "\u2022organic",
2137
+ "\u2022xxxx",
2138
+ "\u2501",
2139
+ "\u253b",
2140
+ "\u253b\u2501\u253b",
2141
+ "\u256f",
2142
+ "\u25a1",
2143
+ "\ufe35",
2144
+ "\uff09"
2145
+ ]
vocab/vectors ADDED
Binary file (128 Bytes). View file
 
vocab/vectors.cfg ADDED
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