whisper-yt-search-query.ipynb

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          "{'matches': [\n",
          "  {'id': 'coaaSxys5so-t129.0',\n",
          "   'metadata': {\n",
          "     'end': 157.0,\n",
          "     'start': 129.0,\n",
          "     'text': \"Let's ask another question. So this one's \"\n",
          "             \"not even really a question. I'm just going \"\n",
          "             'to say OpenAI Clip. And what I want to do '\n",
          "             'is just say okay can you summarize what '\n",
          "             'OpenAI Clip is.',\n",
          "     'title': 'How to build next-level Q&A with OpenAI',\n",
          "     'url': 'https://youtu.be/coaaSxys5so'},\n",
          "   'score': 33.6478119,\n",
          "   'values': []},\n",
          "  {'id': 'coaaSxys5so-t147.0',\n",
          "   'metadata': {\n",
          "     'end': 183.0,\n",
          "     'start': 147.0,\n",
          "     'text': \"So we'll come down here. Let's see what it \"\n",
          "             'returns. Cool so OpenAI Clip is a '\n",
          "             'contrastive language image pre-training '\n",
          "             'model that uses pairs of images and text '\n",
          "             'and returns a matrix of cosine similarity '\n",
          "             \"between text and each image. Okay that's \"\n",
          "             'cool. So written in PyTorch uses bcelas.',\n",
          "     'title': 'How to build next-level Q&A with OpenAI',\n",
          "     'url': 'https://youtu.be/coaaSxys5so'},\n",
          "   'score': 31.5986061,\n",
          "   'values': []},\n",
          "  {'id': 'bVZJ_O_-t2085.44',\n",
          "   'metadata': {\n",
          "     'end': 2131.7599999999998,\n",
          "     'start': 2085.44,\n",
          "     'text': \"OpenAI clip VIT so it's the vision \"\n",
          "             'transformer this VIT you see here refers '\n",
          "             'to the the vision transformer which clip '\n",
          "             'is using or is based on at least the '\n",
          "             'vision aspect and we want to write base '\n",
          "             \"patch 32. So I mean we'll go into more \"\n",
          "             'detail but the patch part of that is '\n",
          "             'referring to the way that the model almost '\n",
          "             'tokenizes your images it splits an image',\n",
          "     'title': 'Intro to Dense Vectors for NLP and Vision',\n",
          "     'url': 'https://youtu.be/bVZJ_O_-0RE'},\n",
          "   'score': 31.4537525,\n",
          "   'values': []},\n",
          "  {'id': '989aKUVBfbk-t35.0',\n",
          "   'metadata': {\n",
          "     'end': 88.5,\n",
          "     'start': 35.0,\n",
          "     'text': 'During pre-training OpenAI trained the '\n",
          "             'model on pairs of images and text and it '\n",
          "             'trained them to both output embedding '\n",
          "             'vectors that are as close as possible to '\n",
          "             'each other. So the text transformer was '\n",
          "             'trained to output a single embedding 512 '\n",
          "             'dimensional embedding that was as close as '\n",
          "             \"possible to the vision transformer's image \"\n",
          "             'embedding for the image text pair. So what '\n",
          "             'that means is that clip is able to take '\n",
          "             'both images and text and embed them both '\n",
          "             'into a similar vector space. And with that '\n",
          "             'we can do a lot of things.',\n",
          "     'title': 'Fast intro to multi-modal ML with '\n",
          "              \"OpenAI's CLIP\",\n",
          "     'url': 'https://youtu.be/989aKUVBfbk'},\n",
          "   'score': 31.4496136,\n",
          "   'values': []},\n",
          "  {'id': '989aKUVBfbk-t98.0',\n",
          "   'metadata': {\n",
          "     'end': 119.0,\n",
          "     'start': 98.0,\n",
          "     'text': 'OpenAI released a GitHub repository OpenAI '\n",
          "             \"clip here. This contains clip but we're \"\n",
          "             'not going to use this implementation. '\n",
          "             \"We're actually going to use this \"\n",
          "             'implementation of clip. So this is on '\n",
          "             'Hugging Face.',\n",
          "     'title': 'Fast intro to multi-modal ML with '\n",
          "              \"OpenAI's CLIP\",\n",
          "     'url': 'https://youtu.be/989aKUVBfbk'},\n",
          "   'score': 29.3169785,\n",
          "   'values': []}],\n",
          " 'namespace': ''}"
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      "source": [
       "query = \"what is OpenAI's CLIP?\"\n",
       "\n",
       "xq = model.encode(query).tolist()\n",
       "\n",
       "index.query(xq, top_k=5, include_metadata=True)"
      ]
     }
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