Update app.py
Browse files
app.py
CHANGED
@@ -25,15 +25,6 @@ dataset = load_dataset("Namitg02/Test", split='train', streaming=False)
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#Returns a list of dictionaries, each representing a row in the dataset.
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print(dataset[1])
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length = len(dataset)
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df = pd.DataFrame(dataset)
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embeddings = embedding_model.encode(dataset["text"])
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print(embeddings)
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df['embeddings'] = embeddings
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dataset = Dataset.from_pandas(df)
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print(dataset[1])
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#Itemdetails = dataset.items()
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#print(Itemdetails)
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@@ -42,6 +33,16 @@ embedding_model = SentenceTransformer("mixedbread-ai/mxbai-embed-large-v1")
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#embedding_model = HuggingFaceEmbeddings(model_name = "mixedbread-ai/mxbai-embed-large-v1")
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#all-MiniLM-L6-v2, BAAI/bge-base-en-v1.5,infgrad/stella-base-en-v2, BAAI/bge-large-en-v1.5 working with default dimensions
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#doc_func = lambda x: x.text
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#dataset = list(map(doc_func, dataset))
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#Returns a list of dictionaries, each representing a row in the dataset.
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print(dataset[1])
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length = len(dataset)
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#Itemdetails = dataset.items()
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#print(Itemdetails)
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#embedding_model = HuggingFaceEmbeddings(model_name = "mixedbread-ai/mxbai-embed-large-v1")
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#all-MiniLM-L6-v2, BAAI/bge-base-en-v1.5,infgrad/stella-base-en-v2, BAAI/bge-large-en-v1.5 working with default dimensions
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df = pd.DataFrame(dataset)
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display(df)
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embeddings = embedding_model.encode(dataset["text"])
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print(embeddings)
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df['embeddings'] = embeddings
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display(df)
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dataset = Dataset.from_pandas(df)
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print(dataset[1])
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print(dataset[2])
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#doc_func = lambda x: x.text
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#dataset = list(map(doc_func, dataset))
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