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Runtime error
Runtime error
Daniel Fried
commited on
Commit
·
fb51e42
1
Parent(s):
5900055
update UI
Browse files- .gitignore +3 -0
- modules/app.py +6 -4
- static/index.html +56 -50
.gitignore
ADDED
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@@ -0,0 +1,3 @@
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use_normal_tokenizers
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__pycache__
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incoder-6B
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modules/app.py
CHANGED
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@@ -5,12 +5,13 @@ import os
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# needs to be imported *before* transformers
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if os.path.exists('use_normal_tokenizers'):
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import tokenizers
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else:
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import tokenizers_patch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import json
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-
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# from flask import Flask, request, render_template
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# from flask_cors import CORS
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# app = Flask(__name__, static_folder='static')
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@@ -24,8 +25,6 @@ import json
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PORT = 7860
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VERBOSE = False
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BIG_MODEL = False
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-
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if BIG_MODEL:
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CUDA = True
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model_name = "facebook/incoder-6B"
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@@ -61,7 +60,10 @@ def generate(input, length_limit=None, temperature=None):
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input_ids = tokenizer(input, return_tensors="pt").input_ids
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if CUDA:
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input_ids = input_ids.cuda()
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-
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detok_hypo_str = tokenizer.decode(output.flatten())
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if detok_hypo_str.startswith(BOS):
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detok_hypo_str = detok_hypo_str[len(BOS):]
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# needs to be imported *before* transformers
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if os.path.exists('use_normal_tokenizers'):
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import tokenizers
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BIG_MODEL = False
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else:
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import tokenizers_patch
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BIG_MODEL = True
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import json
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# from flask import Flask, request, render_template
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# from flask_cors import CORS
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# app = Flask(__name__, static_folder='static')
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PORT = 7860
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VERBOSE = False
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if BIG_MODEL:
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CUDA = True
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model_name = "facebook/incoder-6B"
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input_ids = tokenizer(input, return_tensors="pt").input_ids
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if CUDA:
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input_ids = input_ids.cuda()
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max_length = length_limit + input_ids.flatten().size(0)
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if max_length > 256:
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max_length = 256
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output = model.generate(input_ids=input_ids, do_sample=True, top_p=0.95, temperature=temperature, max_length=max_length)
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detok_hypo_str = tokenizer.decode(output.flatten())
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if detok_hypo_str.startswith(BOS):
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detok_hypo_str = detok_hypo_str[len(BOS):]
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static/index.html
CHANGED
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@@ -124,41 +124,9 @@ label {
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<span><a href='javascript:select_example("metadata-prediction");'>Metadata Prediction</a></span>
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<span><a href='javascript:select_example("humaneval");'>Docstring->Code</a></span>
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</div>
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<div>
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Syntax:
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<select name="mode" id="mode">
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<option value="text">Text</option>
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<option value="c_cpp">C/C++</option>
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<option value="csharp">C#</option>
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<option value="clojure">Clojure</option>
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<option value="coffee">CoffeeScript</option>
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<option value="golang">Go</option>
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<option value="haskell">Haskell</option>
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<option value="java">Java</option>
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<option value="javascript">JavaScript</option>
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<option value="lua">Lua</option>
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<option value="objectivec">Objective C</option>
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<option value="perl">Perl</option>
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<option value="php">PHP</option>
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<option value="python">Python</option>
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<option value="ruby">Ruby</option>
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<option value="rust">Rust</option>
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<option value="scala">Scala</option>
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<option value="sh">Shell</option>
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<option value="swift">Swift</option>
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<option value="typescript">Typescript</option>
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</select>
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</div>
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<div class="request">
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<form id="generate-form">
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<div class="leftside">
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<!--
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<textarea name="prompt" rows="12" cols="100" id="textbox"></textarea>
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<textarea name="prefix" rows="12" cols="100" id="textbox"></textarea>
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<textarea name="suffix" rows="12" cols="100" id="textbox"></textarea>
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-->
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<div id="editor"></div>
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</div>
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<div class="rightside">
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<div>
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<label>Response Length:</label>
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>
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<output>0.6</output>
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</div>
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<!--
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<div>
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<label>Top-k:</label>
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<input type="range" value="2" min="1" max="8" step="1" class="slider"
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oninput="this.nextElementSibling.value = this.value" name="topk">
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<output>2</output>
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</div>
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-->
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<div class="submit-holder">
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<!-- <input type="submit" value="Extend" id="extend-form-button"/> -->
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<input type="button" value="Extend" id="extend-form-button"/>
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<span style='margin-left:1em'>
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<div>
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-->
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</div>
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<div id="error"></div>
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</div>
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</div>
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<div id="loader_holder">
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<div class="loader"></div>
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<div>
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-
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</div>
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</div>
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</div>
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<h3 id="debug-info">
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<p>
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<script type="text/javascript">
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// these constants are only used for providing user expectations.
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var OVERHEAD = 3;
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var EXAMPLES = {
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"python": {
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"prompt": "<| file ext=.py |>\nclass Person:\n" + SPLIT_TOKEN + "\np = Person('Eren', 18, 'Male')",
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-
"length":
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"mode": "python"
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},
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"python-infill2": {
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"""Count the number of occurrences of each word in the file."""
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<infill>
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`,
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"length":
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"mode": "python"
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},
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word_counts[word] = 1
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return word_counts
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`,
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"length":
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"mode": "python"
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},
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"docstring": {
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word_counts[word] = 1
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return word_counts
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`,
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-
"length":
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"mode": "python"
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},
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"javascript": {
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"prompt": "<| file ext=.js |>\n // is something really happening here",
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"length":
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"mode": "javascript"
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},
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"jupyter": {
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"prompt": "<| file ext=.ipynb:python |>\n<text>\nThis notebook demonstrates using scikit-learn to perform PCA.\n</text>\n<cell>",
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"length":
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"mode": "python"
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},
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"stackoverflow": {
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"prompt": "<| q tags=regex,html |>\nParsing HTML with regular expressions\nHow do I do this? Is it a good idea?\n<|/ q dscore=3 |>\n<| a dscore=4 |>",
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-
"length":
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"mode": "text"
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},
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"metadata-conditioning": {
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"prompt": "<| file ext=.py filename=train_model.py source=github dstars=4 |>\n",
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"length":
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"mode": "python"
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},
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"metadata-prediction": {
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<span><a href='javascript:select_example("metadata-prediction");'>Metadata Prediction</a></span>
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<span><a href='javascript:select_example("humaneval");'>Docstring->Code</a></span>
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</div>
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</div>
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<div class="request">
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<form id="generate-form">
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<div class="rightside">
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<div>
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<label>Response Length:</label>
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>
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<output>0.6</output>
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</div>
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<div>
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<!-- <input type="submit" value="Extend" id="extend-form-button"/> -->
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<input type="button" value="Extend" id="extend-form-button"/>
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<span style='margin-left:1em'>
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<div>
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-->
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</div>
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+
<br>
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<div class="leftside">
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<!--
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<textarea name="prompt" rows="12" cols="100" id="textbox"></textarea>
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<textarea name="prefix" rows="12" cols="100" id="textbox"></textarea>
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<textarea name="suffix" rows="12" cols="100" id="textbox"></textarea>
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-->
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<div>
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Syntax:
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<select name="mode" id="mode">
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<option value="text">Text</option>
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<option value="c_cpp">C/C++</option>
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<option value="csharp">C#</option>
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<option value="clojure">Clojure</option>
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<option value="coffee">CoffeeScript</option>
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<option value="golang">Go</option>
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<option value="haskell">Haskell</option>
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<option value="java">Java</option>
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<option value="javascript">JavaScript</option>
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<option value="lua">Lua</option>
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<option value="objectivec">Objective C</option>
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<option value="perl">Perl</option>
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<option value="php">PHP</option>
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<option value="python">Python</option>
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<option value="ruby">Ruby</option>
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<option value="rust">Rust</option>
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<option value="scala">Scala</option>
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<option value="sh">Shell</option>
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<option value="swift">Swift</option>
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<option value="typescript">Typescript</option>
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</select>
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<div id="editor"></div>
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</div>
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<div id="error"></div>
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</div>
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</div>
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<div id="loader_holder">
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<div class="loader"></div>
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<div>
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Generation queued, please wait...
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</div>
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</div>
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</div>
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<h3 id="debug-info">More Info</h3>
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<p>
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This is a demo interface for <a href="https://github.com/dpfried/incoder/blob/main/paper/InCoder-4-12-22.pdf">InCoder: A Generative Model for Code In-Filling and Synthesis</a>.
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</p>
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<p>
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See <a href="https://sites.google.com/view/incoder-code-models">our project site</a> for more information on these models, including a paper and examples.
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</p>
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<p>
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For instructions on setting up and using the models yourself, see <a href="https://github.com/dpfried/incoder/blob/main/README.md">our readme</a>.
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</p>
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<h3 id="debug-info">Credits</h3>
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<p>Model development: Daniel Fried*, Armen Aghajanyan*, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, and Mike Lewis</p>
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<p>Thanks to Naman Goyal and Stephen Roller for writing the code this was based on. Extensions by Daniel Fried and Sida Wang.</p>
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<script type="text/javascript">
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// these constants are only used for providing user expectations.
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var OVERHEAD = 3;
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var EXAMPLES = {
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"python": {
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"prompt": "<| file ext=.py |>\nclass Person:\n" + SPLIT_TOKEN + "\np = Person('Eren', 18, 'Male')",
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+
"length": 64,
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"mode": "python"
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},
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"python-infill2": {
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"""Count the number of occurrences of each word in the file."""
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<infill>
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`,
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+
"length": 64,
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"mode": "python"
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},
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word_counts[word] = 1
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return word_counts
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`,
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+
"length": 4,
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"mode": "python"
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},
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"docstring": {
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word_counts[word] = 1
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return word_counts
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`,
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"length": 32,
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"mode": "python"
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},
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"javascript": {
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"prompt": "<| file ext=.js |>\n // is something really happening here",
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+
"length": 64,
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"mode": "javascript"
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},
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"jupyter": {
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"prompt": "<| file ext=.ipynb:python |>\n<text>\nThis notebook demonstrates using scikit-learn to perform PCA.\n</text>\n<cell>",
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"length": 64,
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"mode": "python"
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},
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"stackoverflow": {
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"prompt": "<| q tags=regex,html |>\nParsing HTML with regular expressions\nHow do I do this? Is it a good idea?\n<|/ q dscore=3 |>\n<| a dscore=4 |>",
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"length": 64,
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"mode": "text"
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},
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"metadata-conditioning": {
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"prompt": "<| file ext=.py filename=train_model.py source=github dstars=4 |>\n",
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"length": 64,
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"mode": "python"
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},
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"metadata-prediction": {
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