McGill-NLP
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LLM2Vec-Mistral-7B-Instruct-v2-mntp-supervised

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vaibhavad commited on Apr 4

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@@ -52,7 +52,6 @@ documents = [
 ]
 d_reps = l2v.encode(documents)
 # Compute cosine similarity
 q_reps_norm = torch.nn.functional.normalize(q_reps, p=2, dim=1)
 d_reps_norm = torch.nn.functional.normalize(d_reps, p=2, dim=1)

 ]
 d_reps = l2v.encode(documents)
 # Compute cosine similarity
 q_reps_norm = torch.nn.functional.normalize(q_reps, p=2, dim=1)
 d_reps_norm = torch.nn.functional.normalize(d_reps, p=2, dim=1)