diff --git a/BigRetriever/1_Pooling/config.json b/BigRetriever/1_Pooling/config.json
deleted file mode 100644
index 4e09f29..0000000
--- a/BigRetriever/1_Pooling/config.json
+++ /dev/null
@@ -1,7 +0,0 @@
-{
-  "word_embedding_dimension": 768,
-  "pooling_mode_cls_token": false,
-  "pooling_mode_mean_tokens": true,
-  "pooling_mode_max_tokens": false,
-  "pooling_mode_mean_sqrt_len_tokens": false
-}
\ No newline at end of file
diff --git a/BigRetriever/README.md b/BigRetriever/README.md
deleted file mode 100644
index f942fae..0000000
--- a/BigRetriever/README.md
+++ /dev/null
@@ -1,129 +0,0 @@
----
-pipeline_tag: sentence-similarity
-tags:
-- sentence-transformers
-- feature-extraction
-- sentence-similarity
-- transformers
-
----
-
-# {MODEL_NAME}
-
-This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
-
-<!--- Describe your model here -->
-
-## Usage (Sentence-Transformers)
-
-Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
-
-```
-pip install -U sentence-transformers
-```
-
-Then you can use the model like this:
-
-```python
-from sentence_transformers import SentenceTransformer
-sentences = ["This is an example sentence", "Each sentence is converted"]
-
-model = SentenceTransformer('{MODEL_NAME}')
-embeddings = model.encode(sentences)
-print(embeddings)
-```
-
-
-
-## Usage (HuggingFace Transformers)
-Without [sentence-transformers](https://www.SBERT.net), you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings.
-
-```python
-from transformers import AutoTokenizer, AutoModel
-import torch
-
-
-#Mean Pooling - Take attention mask into account for correct averaging
-def mean_pooling(model_output, attention_mask):
-    token_embeddings = model_output[0] #First element of model_output contains all token embeddings
-    input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
-    return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)
-
-
-# Sentences we want sentence embeddings for
-sentences = ['This is an example sentence', 'Each sentence is converted']
-
-# Load model from HuggingFace Hub
-tokenizer = AutoTokenizer.from_pretrained('{MODEL_NAME}')
-model = AutoModel.from_pretrained('{MODEL_NAME}')
-
-# Tokenize sentences
-encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')
-
-# Compute token embeddings
-with torch.no_grad():
-    model_output = model(**encoded_input)
-
-# Perform pooling. In this case, mean pooling.
-sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask'])
-
-print("Sentence embeddings:")
-print(sentence_embeddings)
-```
-
-
-
-## Evaluation Results
-
-<!--- Describe how your model was evaluated -->
-
-For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name={MODEL_NAME})
-
-
-## Training
-The model was trained with the parameters:
-
-**DataLoader**:
-
-`sentence_transformers.datasets.NoDuplicatesDataLoader.NoDuplicatesDataLoader` of length 21515 with parameters:
-```
-{'batch_size': 8}
-```
-
-**Loss**:
-
-`sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss` with parameters:
-  ```
-  {'scale': 20.0, 'similarity_fct': 'cos_sim'}
-  ```
-
-Parameters of the fit()-Method:
-```
-{
-    "epochs": 5,
-    "evaluation_steps": 0,
-    "evaluator": "NoneType",
-    "max_grad_norm": 1,
-    "optimizer_class": "<class 'torch.optim.adamw.AdamW'>",
-    "optimizer_params": {
-        "lr": 2e-05
-    },
-    "scheduler": "WarmupLinear",
-    "steps_per_epoch": null,
-    "warmup_steps": 10757,
-    "weight_decay": 0.01
-}
-```
-
-
-## Full Model Architecture
-```
-SentenceTransformer(
-  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: MPNetModel 
-  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
-)
-```
-
-## Citing & Authors
-
-<!--- Describe where people can find more information -->
\ No newline at end of file
diff --git a/BigRetriever/config.json b/BigRetriever/config.json
deleted file mode 100644
index 23bbec8..0000000
--- a/BigRetriever/config.json
+++ /dev/null
@@ -1,24 +0,0 @@
-{
-  "_name_or_path": "microsoft/mpnet-base",
-  "architectures": [
-    "MPNetModel"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "bos_token_id": 0,
-  "eos_token_id": 2,
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-05,
-  "max_position_embeddings": 514,
-  "model_type": "mpnet",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "pad_token_id": 1,
-  "relative_attention_num_buckets": 32,
-  "torch_dtype": "float32",
-  "transformers_version": "4.20.1",
-  "vocab_size": 30527
-}
diff --git a/BigRetriever/config_sentence_transformers.json b/BigRetriever/config_sentence_transformers.json
deleted file mode 100644
index e2fa6e5..0000000
--- a/BigRetriever/config_sentence_transformers.json
+++ /dev/null
@@ -1,7 +0,0 @@
-{
-  "__version__": {
-    "sentence_transformers": "2.2.2",
-    "transformers": "4.20.1",
-    "pytorch": "1.12.0"
-  }
-}
\ No newline at end of file
diff --git a/BigRetriever/modules.json b/BigRetriever/modules.json
deleted file mode 100644
index f7640f9..0000000
--- a/BigRetriever/modules.json
+++ /dev/null
@@ -1,14 +0,0 @@
-[
-  {
-    "idx": 0,
-    "name": "0",
-    "path": "",
-    "type": "sentence_transformers.models.Transformer"
-  },
-  {
-    "idx": 1,
-    "name": "1",
-    "path": "1_Pooling",
-    "type": "sentence_transformers.models.Pooling"
-  }
-]
\ No newline at end of file
diff --git a/BigRetriever/sentence_bert_config.json b/BigRetriever/sentence_bert_config.json
deleted file mode 100644
index f789d99..0000000
--- a/BigRetriever/sentence_bert_config.json
+++ /dev/null
@@ -1,4 +0,0 @@
-{
-  "max_seq_length": 512,
-  "do_lower_case": false
-}
\ No newline at end of file
diff --git a/BigRetriever/special_tokens_map.json b/BigRetriever/special_tokens_map.json
deleted file mode 100644
index 2eb83d0..0000000
--- a/BigRetriever/special_tokens_map.json
+++ /dev/null
@@ -1,15 +0,0 @@
-{
-  "bos_token": "<s>",
-  "cls_token": "<s>",
-  "eos_token": "</s>",
-  "mask_token": {
-    "content": "<mask>",
-    "lstrip": true,
-    "normalized": false,
-    "rstrip": false,
-    "single_word": false
-  },
-  "pad_token": "<pad>",
-  "sep_token": "</s>",
-  "unk_token": "[UNK]"
-}
diff --git a/BigRetriever/tokenizer.json b/BigRetriever/tokenizer.json
deleted file mode 100644
index 9daf87c..0000000
--- a/BigRetriever/tokenizer.json
+++ /dev/null
@@ -1,30636 +0,0 @@
-{
-  "version": "1.0",
-  "truncation": {
-    "direction": "Right",
-    "max_length": 512,
-    "strategy": "LongestFirst",
-    "stride": 0
-  },
-  "padding": {
-    "strategy": "BatchLongest",
-    "direction": "Right",
-    "pad_to_multiple_of": null,
-    "pad_id": 1,
-    "pad_type_id": 0,
-    "pad_token": "<pad>"
-  },
-  "added_tokens": [
-    {
-      "id": 0,
-      "content": "<s>",
-      "single_word": false,
-      "lstrip": false,
-      "rstrip": false,
-      "normalized": false,
-      "special": true
-    },
-    {
-      "id": 1,
-      "content": "<pad>",
-      "single_word": false,
-      "lstrip": false,
-      "rstrip": false,
-      "normalized": false,
-      "special": true
-    },
-    {
-      "id": 2,
-      "content": "</s>",
-      "single_word": false,
-      "lstrip": false,
-      "rstrip": false,
-      "normalized": false,
-      "special": true
-    },
-    {
-      "id": 3,
-      "content": "<unk>",
-      "single_word": false,
-      "lstrip": false,
-      "rstrip": false,
-      "normalized": true,
-      "special": true
-    },
-    {
-      "id": 104,
-      "content": "[UNK]",
-      "single_word": false,
-      "lstrip": false,
-      "rstrip": false,
-      "normalized": false,
-      "special": true
-    },
-    {
-      "id": 30526,
-      "content": "<mask>",
-      "single_word": false,
-      "lstrip": true,
-      "rstrip": false,
-      "normalized": false,
-      "special": true
-    }
-  ],
-  "normalizer": {
-    "type": "BertNormalizer",
-    "clean_text": true,
-    "handle_chinese_chars": true,
-    "strip_accents": null,
-    "lowercase": true
-  },
-  "pre_tokenizer": {
-    "type": "BertPreTokenizer"
-  },
-  "post_processor": {
-    "type": "RobertaProcessing",
-    "sep": [
-      "</s>",
-      2
-    ],
-    "cls": [
-      "<s>",
-      0
-    ],
-    "trim_offsets": true,
-    "add_prefix_space": false
-  },
-  "decoder": {
-    "type": "WordPiece",
-    "prefix": "##",
-    "cleanup": true
-  },
-  "model": {
-    "type": "WordPiece",
-    "unk_token": "[UNK]",
-    "continuing_subword_prefix": "##",
-    "max_input_chars_per_word": 100,
-    "vocab": {
-      "<s>": 0,
-      "<pad>": 1,
-      "</s>": 2,
-      "<unk>": 3,
-      "[PAD]": 4,
-      "[unused0]": 5,
-      "[unused1]": 6,
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\ No newline at end of file
diff --git a/BigRetriever/tokenizer_config.json b/BigRetriever/tokenizer_config.json
deleted file mode 100644
index d0f237f..0000000
--- a/BigRetriever/tokenizer_config.json
+++ /dev/null
@@ -1,16 +0,0 @@
-{
-  "bos_token": "<s>",
-  "cls_token": "<s>",
-  "do_lower_case": true,
-  "eos_token": "</s>",
-  "mask_token": "<mask>",
-  "model_max_length": 512,
-  "name_or_path": "microsoft/mpnet-base",
-  "pad_token": "<pad>",
-  "sep_token": "</s>",
-  "special_tokens_map_file": null,
-  "strip_accents": null,
-  "tokenize_chinese_chars": true,
-  "tokenizer_class": "MPNetTokenizer",
-  "unk_token": "[UNK]"
-}
diff --git a/BigRetriever/vocab.txt b/BigRetriever/vocab.txt
deleted file mode 100644
index 1c51ab7..0000000
--- a/BigRetriever/vocab.txt
+++ /dev/null
@@ -1,30527 +0,0 @@
-<s>
-<pad>
-</s>
-<unk>
-[PAD]
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-[UNK]
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-!
-"
-#
-$
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-&
-'
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-)
-*
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-,
--
-.
-/
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-9
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->
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-[
-\
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-լ
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-տ
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-ւ
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-־
-א
-ב
-ג
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-length
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-fingers
-command
-staff
-skin
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-medal
-kill
-sun
-cover
-job
-1985
-introduced
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-hell
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-##ies
-success
-meet
-reason
-standard
-meeting
-novel
-1984
-trade
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-buildings
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-rose
-guy
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-chapter
-native
-husband
-previously
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-limited
-entered
-weeks
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-mountain
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-covered
-forced
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-complete
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-cold
-##ya
-channel
-1980
-traditional
-films
-dance
-clear
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-500
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-prince
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-silver
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-operation
-##ine
-economic
-1983
-holding
-twenty
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-additional
-speed
-hour
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-regular
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-whom
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-movie
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-prior
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-1982
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-contract
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-couple
-stand
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-executive
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-1979
-hope
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-plays
-defeated
-municipality
-whether
-structure
-offered
-slowly
-pain
-ice
-direction
-##ion
-paper
-mission
-1981
-mostly
-200
-noted
-individual
-managed
-nature
-lives
-plant
-##ha
-helped
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-1972
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-male
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-problem
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-1976
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-1978
-surface
-caused
-italy
-understand
-greek
-highway
-wrong
-hotel
-comes
-appearance
-joseph
-double
-issues
-musical
-companies
-castle
-income
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-assembly
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-initially
-parliament
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-1974
-particular
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-1975
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-1970
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-1968
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-1945
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-2nd
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-45
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-1967
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-35
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-poor
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-mile
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-1964
-1966
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-1965
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-numbers
-digital
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-1960
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-individuals
-hundred
-weight
-creek
-sleep
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-provides
-ordered
-code
-value
-jewish
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-1944
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-whatever
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-machine
-1963
-territory
-mainly
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-squadron
-1962
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-iron
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-headed
-ability
-promoted
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-1942
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-80
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-pressure
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-newspaper
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-chris
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-firm
-maria
-amount
-mixed
-daniel
-proposed
-perfect
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-3rd
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-contemporary
-paid
-1943
-prison
-save
-kitchen
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-administrative
-intended
-constructed
-academic
-nice
-teacher
-races
-1956
-formerly
-corporation
-ben
-nation
-issued
-shut
-1958
-drums
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-seems
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-1959
-graduated
-function
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-picked
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-exchange
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-1980s
-loved
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-fish
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-1941
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-1940
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-1948
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-1957
-risk
-tonight
-positive
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-singles
-effects
-gray
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-1939
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-1946
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-1950
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-visit
-33
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-search
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-buried
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-1970s
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-1952
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-44
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-36
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-1954
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-1949
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-1960s
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-1951
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-1990s
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-1936
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-1920
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-48
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