Upload Orpheus_Auto_Continuations_Generator.ipynb
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inference_code/Orpheus_Auto_Continuations_Generator.ipynb
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@@ -344,6 +344,7 @@
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"temperature = 1.0\n",
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"top_p_value = 0.96\n",
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"num_mem_tokens = 7168 # up to 12 chunks\n",
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"\n",
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"# Advanced options\n",
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"max_tok_rep_ratio = 0.95\n",
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@@ -377,9 +378,9 @@
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" \n",
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" inp = torch.LongTensor(y).cuda()\n",
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" \n",
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" \n",
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" scores = cosine_similarity(embeddings,
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"\n",
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" scores = [o for o in scores if o != max(scores)]\n",
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"\n",
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@@ -484,9 +485,9 @@
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" \n",
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" inp = torch.LongTensor([song]).cuda()\n",
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" \n",
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" \n",
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" start_score = cosine_similarity(embeddings,
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"\n",
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" b_size = batch_size\n",
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" stop = False\n",
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@@ -529,8 +530,13 @@
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" inp = torch.LongTensor(output).cuda()\n",
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" \n",
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" embs = get_embeddings(inp)\n",
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" output_scores.extend(scores)\n",
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" \n",
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" scores = [o for o in output_scores if o != max(output_scores)]\n",
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"temperature = 1.0\n",
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"top_p_value = 0.96\n",
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"num_mem_tokens = 7168 # up to 12 chunks\n",
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"use_prime_embeddings = False\n",
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"\n",
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"# Advanced options\n",
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"max_tok_rep_ratio = 0.95\n",
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" \n",
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" inp = torch.LongTensor(y).cuda()\n",
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" \n",
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" prime_embs = get_embeddings(inp)\n",
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" \n",
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" scores = cosine_similarity(embeddings, prime_embs).max(axis=0)\n",
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"\n",
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" scores = [o for o in scores if o != max(scores)]\n",
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"\n",
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" \n",
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" inp = torch.LongTensor([song]).cuda()\n",
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" \n",
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" prime_embs = get_embeddings(inp)\n",
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" \n",
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" start_score = cosine_similarity(embeddings, prime_embs).max(axis=0)[0]\n",
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"\n",
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" b_size = batch_size\n",
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" stop = False\n",
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" inp = torch.LongTensor(output).cuda()\n",
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" \n",
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" embs = get_embeddings(inp)\n",
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"\n",
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" if use_prime_embeddings:\n",
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" scores = cosine_similarity(prime_embs, embs).max(axis=0) \n",
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"\n",
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" else:\n",
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" scores = cosine_similarity(embeddings, embs).max(axis=0)\n",
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" \n",
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" output_scores.extend(scores)\n",
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" \n",
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" scores = [o for o in output_scores if o != max(output_scores)]\n",
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