andras/great-ai
1
0
Fork 0
Code Issues Pull requests 1 Projects Releases 4 Packages Wiki Activity Actions

Deployed aa31d2b with MkDocs version: 1.3.0

Browse source
This commit is contained in:
2022-07-15 15:52:07 +00:00
parent 5a8662103a
commit 087e049514
17 changed files with 58 additions and 64 deletions
Download patch file Download diff file Expand all files Collapse all files

2
examples/simple/data/data.ipynb
View file

@ -103,9 +103,7 @@
" unchunk,\n",
")\n",
"\n",
"\n",
"def preprocess_chunk(chunk_key: str) -> List[Tuple[str, List[str]]]:\n",
" # Extract\n",
" response = urllib.request.urlopen(\n",
" f\"https://s3-us-west-2.amazonaws.com/ai2-s2-research-public/\"\n",
" \"open-corpus/2022-02-01/{chunk_key}\"\n",

6
examples/simple/data/index.html
View file

@ -2083,9 +2083,7 @@ f"""Processing {len(chunks)} out of the {
<span class="n">unchunk</span><span class="p">,</span>
<span class="p">)</span>
<span class="k">def</span> <span class="nf">preprocess_chunk</span><span class="p">(</span><span class="n">chunk_key</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">List</span><span class="p">[</span><span class="n">Tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">]]]:</span>
<span class="c1"># Extract</span>
<span class="n">response</span> <span class="o">=</span> <span class="n">urllib</span><span class="o">.</span><span class="n">request</span><span class="o">.</span><span class="n">urlopen</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;https://s3-us-west-2.amazonaws.com/ai2-s2-research-public/&quot;</span>
<span class="s2">&quot;open-corpus/2022-02-01/</span><span class="si">{chunk_key}</span><span class="s2">&quot;</span>
@ -2125,9 +2123,7 @@ from great_ai.utilities import (
unchunk,
)
def preprocess_chunk(chunk_key: str) -> List[Tuple[str, List[str]]]:
# Extract
response = urllib.request.urlopen(
f"https://s3-us-west-2.amazonaws.com/ai2-s2-research-public/"
"open-corpus/2022-02-01/{chunk_key}"
@ -2294,7 +2290,7 @@ add_ground_truth(X, y, train_split_ratio=0.8, test_split_ratio=0.2)</div>
<small>
Last update:
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 12, 2022</span>
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 15, 2022</span>
</small>

4
examples/simple/train/index.html
View file

@ -1877,7 +1877,7 @@ Licensed under the Apache License, Version 2.0.
<blockquote><p>The blue boxes show the steps implemented in this notebook.</p>
</blockquote>
<p>In the first part, we have cleaned and transformed our training data. We can now access this data using <code>great_ai.LargeFile</code>. Locally, it will gives us the cached version, otherwise, the latest version is downloaded from S3 or GridFS.</p>
<p>In this part, we hyperparameter-optimise and train a simple, Naive Bayes classifier which we then export for deployment using <code>great_ai.save_model</code>.</p>
<p>In this part, we hyperparameter-optimise and train a simple Naive Bayes classifier which we then export for deployment using <code>great_ai.save_model</code>.</p>
<h2 id="load-data-that-has-been-extracted-in-part-1">Load data that has been extracted in <a href="/examples/simple/data">part 1</a><a class="anchor-link" href="#load-data-that-has-been-extracted-in-part-1">&#182;</a></h2>
</div>
</div>
@ -2864,7 +2864,7 @@ save_model(classifier, key="small-domain-prediction", keep_last_n=5)</div>
<small>
Last update:
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 12, 2022</span>
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 15, 2022</span>
</small>

2
examples/simple/train/train.ipynb
View file

@ -11,7 +11,7 @@
"\n",
"In the first part, we have cleaned and transformed our training data. We can now access this data using `great_ai.LargeFile`. Locally, it will gives us the cached version, otherwise, the latest version is downloaded from S3 or GridFS. \n",
"\n",
"In this part, we hyperparameter-optimise and train a simple, Naive Bayes classifier which we then export for deployment using `great_ai.save_model`.\n",
"In this part, we hyperparameter-optimise and train a simple Naive Bayes classifier which we then export for deployment using `great_ai.save_model`.\n",
"\n",
"## Load data that has been extracted in [part 1](/examples/simple/data)"
]