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  import torch
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  from transformers import AutoModel, AutoTokenizer, LlamaModel
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  # compute similarity score
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  score = query_embedding @ passage_embeddings.T
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  print(score)
 
 
 
 
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+ # LLARA-7B-Passage
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+ This model is fine-tuned from LLaMA-2-7B using LoRA and the embedding size is 4096.
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+ ## Training Data
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+ The model is fine-tuned on the training split of [MS MARCO Passage Ranking](https://microsoft.github.io/msmarco/Datasets) datasets for 1 epoch. Please check our paper for details.
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+ ## Usage
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+ Below is an example to encode a query and a passage, and then compute their similarity using their embedding.
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+ ```python
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  import torch
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  from transformers import AutoModel, AutoTokenizer, LlamaModel
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  # compute similarity score
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  score = query_embedding @ passage_embeddings.T
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  print(score)
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+ ```