Server funtional
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@ -3,7 +3,9 @@ from sentence_transformers import SentenceTransformer
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# uno de uso gereal el de mejor desempeño all-mpnet-base-v2
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# uno de uso gereal el de mejor desempeño all-mpnet-base-v2
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# el mas rapido "paraphrase-MiniLM-L3-v2" y "all-MiniLM-L6-v2"
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# el mas rapido "paraphrase-MiniLM-L3-v2" y "all-MiniLM-L6-v2"
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# muy rappudo y muy acertado "all-MiniLM-L12-v2"
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# muy rappudo y muy acertado "all-MiniLM-L12-v2"
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models=["all-MiniLM-L12-v2","paraphrase-MiniLM-L3-v2" , "all-MiniLM-L6-v2","all-mpnet-base-v2","multi-qa-mpnet-base-dot-v1"]
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#models=["all-MiniLM-L12-v2","paraphrase-MiniLM-L3-v2" , "all-MiniLM-L6-v2",
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models=["all-mpnet-base-v2","multi-qa-mpnet-base-dot-v1"]
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for model in models:
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for model in models:
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modelST = SentenceTransformer(model)
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modelST = SentenceTransformer(model)
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# Define the path where you want to save the model
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# Define the path where you want to save the model
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2
main.py
2
main.py
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@ -91,7 +91,7 @@ def loadmodelEmb(model_name = "embeddings/all-MiniLM-L6-v2",model_kwargs = {'dev
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st = SentenceTransformer(model_name)
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st = SentenceTransformer(model_name)
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return st
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return st
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emb=loadmodelEmb()
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#emb=loadmodelEmb()
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CUSTOM_PATH = "/angela"
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CUSTOM_PATH = "/angela"
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app = FastAPI()
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app = FastAPI()
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