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James Briggs
2023-08-02 21:31:20 +08:00
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docs/gen-qa-openai-fast.ipynb → docs/gen-qa-openai.ipynb
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@@ -7,7 +7,7 @@
"id": "SMFUgtvbFeLQ"
},
"source": [
"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/gen-qa-openai-fast.ipynb) [![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/docs/gen-qa-openai-fast.ipynb)"
"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/gen-qa-openai.ipynb) [![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/docs/gen-qa-openai.ipynb)"
]
},
{
@@ -21,8 +21,6 @@
"\n",
"#### Fixing LLMs that Hallucinate\n",
"\n",
"[![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/full-link.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/gen-qa-openai-fast.ipynb)\n",
"\n",
"In this notebook we will learn how to query relevant contexts to our queries from Pinecone, and pass these to a generative OpenAI model to generate an answer backed by real data sources. Required installs for this notebook are:"
]
},
@@ -80,7 +78,7 @@
"\n",
"There are many options for creating these dense vectors, like open source [sentence transformers](https://pinecone.io/learn/nlp/) or OpenAI's [ada-002 model](https://youtu.be/ocxq84ocYi0). We will use OpenAI's offering in this example.\n",
"\n",
"We have already precomputed the embeddings here to speed things up. If you'd like to work through the full process however, check out [this notebook](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/gen-qa-openai-fast.ipynb).\n",
"We have already precomputed the embeddings here to speed things up. If you'd like to work through the full process however, check out [this notebook](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/gen-qa-openai.ipynb).\n",
"\n",
"To download our precomputed embeddings we use Pinecone datasets:"
]