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import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "flax-community/gpt-code-clippy-125M-apps-alldata"
model = AutoModelForCausalLM.from_pretrained(model_name, from_flax=True)
tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-125M")
tokenizer.pad_token = tokenizer.eos_token
def format_input(question, starter_code=""):
answer_type = "\nUse Call-Based format\n" if starter_code else "\nUse Standard Input format\n"
return f"\nQUESTION:\n{question}\n{starter_code}\n{answer_type}\nANSWER:\n"
def format_outputs(text):
formatted_text =f'''
<head>
<link rel="stylesheet"
href="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/10.0.3/styles/default.min.css">
<script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/10.0.3/highlight.min.js"></script>
<script>hljs.initHighlightingOnLoad();</script>
</head>
<body>
<pre><code class="python">{text}</code></pre>
</body>
'''
return formatted_text
def generate_solution(question, starter_code="", temperature=1., num_beams=1):
prompt = format_input(question, starter_code)
input_ids = tokenizer(prompt, return_tensors="pt").input_ids
start = len(input_ids[0])
output = model.generate(
input_ids,
max_length=start+200,
do_sample=True,
top_p=0.95,
pad_token_id=tokenizer.pad_token_id,
early_stopping=True,
temperature=1.,
num_beams=int(num_beams),
no_repeat_ngram_size=None,
repetition_penalty=None,
num_return_sequences=None,
)
return format_outputs(tokenizer.decode(output[0][start:]).strip())
_EXAMPLES = [
[
"""
Given a 2D list of size `m * n`. Your task is to find the sum of minimum value in each row.
For Example:
```python
[
[1, 2, 3, 4, 5], # minimum value of row is 1
[5, 6, 7, 8, 9], # minimum value of row is 5
[20, 21, 34, 56, 100] # minimum value of row is 20
]
```
So, the function should return `26` because sum of minimums is as `1 + 5 + 20 = 26`
""",
"",
0.8,
],
[
"""
# Personalized greeting
Create a function that gives a personalized greeting. This function takes two parameters: `name` and `owner`.
""",
"""
Use conditionals to return the proper message:
case| return
--- | ---
name equals owner | 'Hello boss'
otherwise | 'Hello guest'
def greet(name, owner):
""",
0.8,
]
]
inputs = [
gr.inputs.Textbox(placeholder="Define a problem here...", lines=7),
gr.inputs.Textbox(placeholder="Provide optional starter code...", lines=3),
gr.inputs.Slider(0.5, 1.5, 0.1, default=0.8, label="Temperature"),
gr.inputs.Slider(1,4,1,default=1, label="Beam size")
]
outputs = [
gr.outputs.HTML(label="Solution")
]
gr.Interface(
generate_solution,
inputs=inputs,
outputs=outputs,
title="Code Clippy: Problem Solver",
examples=_EXAMPLES,
).launch(share=False)
|