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Update README.md
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README.md
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@@ -374,8 +374,8 @@ import torch
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from transformers import AutoModelForSequenceClassification, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained('BAAI/bge-reranker-large')
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model = AutoModelForSequenceClassification.from_pretrained('BAAI/bge-reranker-
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model_ort =
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# Sentences we want sentence embeddings for
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pairs = [['what is panda?', 'hi'], ['what is panda?', 'The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China.']]
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@@ -401,7 +401,7 @@ query='what is panda?'
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docs = ['The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear', "Paris is in France."]
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engine = AsyncEmbeddingEngine.from_args(
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EngineArgs(model_name_or_path = "BAAI/bge-
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))
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async def main():
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from transformers import AutoModelForSequenceClassification, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained('BAAI/bge-reranker-large')
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model = AutoModelForSequenceClassification.from_pretrained('BAAI/bge-reranker-base')
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model_ort = ORTModelForSequenceClassification.from_pretrained('BAAI/bge-reranker-base', file_name="onnx/model.onnx")
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# Sentences we want sentence embeddings for
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pairs = [['what is panda?', 'hi'], ['what is panda?', 'The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China.']]
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docs = ['The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear', "Paris is in France."]
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engine = AsyncEmbeddingEngine.from_args(
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EngineArgs(model_name_or_path = "BAAI/bge-reranker-base", device="cpu", engine="optimum" # or engine="torch"
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))
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async def main():
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