Tested notebook end to end

pull/1077/head
colin-openai 2 years ago
parent d93ce7bb48
commit 6d0203788c

@ -63,7 +63,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 1,
"id": "5be94df6",
"metadata": {},
"outputs": [],
@ -111,7 +111,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 2,
"id": "bd99e08e",
"metadata": {},
"outputs": [],
@ -172,10 +172,32 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 3,
"id": "0c1c73cb",
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Found cached dataset wikipedia (/Users/colin.jarvis/.cache/huggingface/datasets/wikipedia/20220301.simple/2.0.0/aa542ed919df55cc5d3347f42dd4521d05ca68751f50dbc32bae2a7f1e167559)\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "6aa3a11d70424916915334e267f4964b",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/1 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# We'll use the datasets library to pull the Simple Wikipedia dataset for embedding\n",
"dataset = list(load_dataset(\"wikipedia\", \"20220301.simple\")[\"train\"])\n",
@ -185,7 +207,7 @@
},
{
"cell_type": "code",
"execution_count": 15,
"execution_count": 12,
"id": "e6ee90ce",
"metadata": {},
"outputs": [
@ -200,15 +222,15 @@
"name": "stderr",
"output_type": "stream",
"text": [
"25024it [01:11, 348.92it/s] "
"25024it [00:59, 423.81it/s] "
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 15.8 s, sys: 1.96 s, total: 17.8 s\n",
"Wall time: 1min 14s\n"
"CPU times: user 17.9 s, sys: 3.15 s, total: 21 s\n",
"Wall time: 1min 1s\n"
]
},
{
@ -227,7 +249,7 @@
},
{
"cell_type": "code",
"execution_count": 16,
"execution_count": 5,
"id": "850c7215",
"metadata": {},
"outputs": [
@ -242,7 +264,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"25024it [00:21, 1164.97it/s] \n"
"25024it [00:40, 616.58it/s] \n"
]
}
],
@ -253,7 +275,7 @@
},
{
"cell_type": "code",
"execution_count": 17,
"execution_count": 13,
"id": "1410daaa",
"metadata": {},
"outputs": [
@ -372,7 +394,7 @@
"4 [0.021524671465158463, 0.018522677943110466, -... 4 "
]
},
"execution_count": 17,
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
@ -406,7 +428,7 @@
},
{
"cell_type": "code",
"execution_count": 18,
"execution_count": 11,
"id": "92e6152a",
"metadata": {},
"outputs": [],
@ -715,7 +737,7 @@
},
{
"cell_type": "code",
"execution_count": 33,
"execution_count": null,
"id": "b9ea472d",
"metadata": {},
"outputs": [],
@ -725,21 +747,10 @@
},
{
"cell_type": "code",
"execution_count": 34,
"execution_count": null,
"id": "13be220d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'classes': []}"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"client.schema.delete_all()\n",
"client.schema.get()"
@ -747,21 +758,10 @@
},
{
"cell_type": "code",
"execution_count": 35,
"execution_count": null,
"id": "73d33184",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"client.is_ready()"
]
@ -1095,7 +1095,7 @@
},
{
"cell_type": "code",
"execution_count": 27,
"execution_count": 7,
"id": "76d697e9",
"metadata": {
"ExecuteTime": {
@ -1110,7 +1110,7 @@
},
{
"cell_type": "code",
"execution_count": 29,
"execution_count": 8,
"id": "1deeb539",
"metadata": {
"ExecuteTime": {
@ -1125,7 +1125,7 @@
"CollectionsResponse(collections=[])"
]
},
"execution_count": 29,
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}

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