mirror of
https://github.com/hwchase17/langchain
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119 lines
2.7 KiB
Plaintext
119 lines
2.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "fff4734f",
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"metadata": {},
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"source": [
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"# TensorflowHub\n",
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"Let's load the TensorflowHub Embedding class."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "f822104b",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.embeddings import TensorflowHubEmbeddings"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "bac84e46",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2023-01-30 23:53:01.652176: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA\n",
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"To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
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"2023-01-30 23:53:34.362802: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA\n",
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"To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
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]
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}
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],
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"source": [
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"embeddings = TensorflowHubEmbeddings()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "4790d770",
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"metadata": {},
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"outputs": [],
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"source": [
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"text = \"This is a test document.\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "f556dcdb",
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"metadata": {},
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"outputs": [],
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"source": [
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"query_result = embeddings.embed_query(text)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "76f1b752",
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"metadata": {},
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"outputs": [],
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"source": [
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"doc_results = embeddings.embed_documents([\"foo\"])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "fff99b21",
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"metadata": {},
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"outputs": [],
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"source": [
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"doc_results"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "aaad49f8",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.1"
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},
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"vscode": {
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"interpreter": {
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"hash": "7377c2ccc78bc62c2683122d48c8cd1fb85a53850a1b1fc29736ed39852c9885"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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