saanikat
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renaming
Browse files- README.md +3 -3
- {bedbase_schema β bedbase}/bedbase_schema_design.yaml +0 -0
- {bedbase_schema β bedbase}/label_encoder_bedbase.pkl +0 -0
- {bedbase_schema β bedbase}/model_bedbase.pth +0 -0
- {bedbase_schema β bedbase}/vectorizer_bedbase.pkl +0 -0
- {encode_schema β encode}/encode_schema_design.yaml +0 -0
- {encode_schema β encode}/label_encoder_encode.pkl +0 -0
- {encode_schema β encode}/model_encode.pth +0 -0
- {encode_schema β encode}/vectorizer_encode.pkl +0 -0
- {fairtracks_schema β fairtracks}/fairtracks_schema_design.yaml +0 -0
- {fairtracks_schema β fairtracks}/label_encoder_fairtracks.pkl +0 -0
- {fairtracks_schema β fairtracks}/model_fairtracks.pth +0 -0
- {fairtracks_schema β fairtracks}/vectorizer_fairtracks.pkl +0 -0
README.md
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@@ -6,17 +6,17 @@ This repository hosts three pre-trained models desgined for metadata attribute s
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```
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/attribute-standardizer-model6
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/
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- bedbase_schema_design.yaml # BEDBASE schema
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- label_encoder_bedbase.pkl # Unqiue label values derived from training data, model classifies the output into these labels for BEDBASE schema
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- model_bedbase.pth # BEDBASE schema trained model
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- vectorizer_bedbase.pkl # CountVectorizer instance from the `scikit-learn` library for Bag of Words encoding used as input to the model
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/
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- encode_schema_design.yaml #ENCODE schema
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- label_encoder_encode.pkl # Unqiue label values derived from training data, model classifies the output into these labels for ENCODE schema
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- model_encode.pth # ENCODE schema trained model
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- vectorizer_encode.pkl # CountVectorizer instance from the `scikit-learn` library for Bag of Words encoding used as input to the model
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/
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- fairtracks_schema_design.yaml # FAIRTRACKS schema
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- label_encoder_fairtracks.pkl # Unqiue label values derived from training data, model classifies the output into these labels for FAIRTRACKS schema
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- model_fairtracks.pth #FAIRTRACKS schema trained model
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```
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/attribute-standardizer-model6
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/bedbase
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- bedbase_schema_design.yaml # BEDBASE schema
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- label_encoder_bedbase.pkl # Unqiue label values derived from training data, model classifies the output into these labels for BEDBASE schema
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- model_bedbase.pth # BEDBASE schema trained model
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- vectorizer_bedbase.pkl # CountVectorizer instance from the `scikit-learn` library for Bag of Words encoding used as input to the model
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/encode
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- encode_schema_design.yaml #ENCODE schema
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- label_encoder_encode.pkl # Unqiue label values derived from training data, model classifies the output into these labels for ENCODE schema
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- model_encode.pth # ENCODE schema trained model
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- vectorizer_encode.pkl # CountVectorizer instance from the `scikit-learn` library for Bag of Words encoding used as input to the model
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/fairtracks
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- fairtracks_schema_design.yaml # FAIRTRACKS schema
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- label_encoder_fairtracks.pkl # Unqiue label values derived from training data, model classifies the output into these labels for FAIRTRACKS schema
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- model_fairtracks.pth #FAIRTRACKS schema trained model
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{bedbase_schema β bedbase}/bedbase_schema_design.yaml
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{bedbase_schema β bedbase}/label_encoder_bedbase.pkl
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{bedbase_schema β bedbase}/model_bedbase.pth
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{bedbase_schema β bedbase}/vectorizer_bedbase.pkl
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{encode_schema β encode}/encode_schema_design.yaml
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{encode_schema β encode}/label_encoder_encode.pkl
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{encode_schema β encode}/model_encode.pth
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{encode_schema β encode}/vectorizer_encode.pkl
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{fairtracks_schema β fairtracks}/fairtracks_schema_design.yaml
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{fairtracks_schema β fairtracks}/label_encoder_fairtracks.pkl
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{fairtracks_schema β fairtracks}/model_fairtracks.pth
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{fairtracks_schema β fairtracks}/vectorizer_fairtracks.pkl
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