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Create app.py
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app.py
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import spaces
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import gradio as gr
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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title = "# 👋🏻Welcome to🌟Tonic's⚖️StableCode2"
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description = """⚖️StableCode2 is a small sized coding llm that performs well in python ! You can also use [⚖️stabilityai/stable-code-3b](https://huggingface.co/stabilityai/stable-code-3b) by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic/stablecode2?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3>
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Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community 👻 [](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to 🌟 [EasyAGI](https://github.com/tonic-ai/EasyAGI) 🤗Big thanks to Ythe folks at huggingface for the ZeroGPU 🤗
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To contribute to this space make a PR with a new example or cool new use-case for this one 🤗
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"""
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tokenizer = AutoTokenizer.from_pretrained(
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"stabilityai/stable-code-3b", trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained(
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"stabilityai/stable-code-3b",
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trust_remote_code=True,
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torch_dtype="auto",
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attn_implementation="flash_attention_2",
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).to("cuda" if torch.cuda.is_available() else "cpu")
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@spaces.GPU
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def generate_code(prompt):
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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tokens = model.generate(
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**inputs,
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max_new_tokens=650,
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temperature=0.3,
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do_sample=False,
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)
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generated_code = tokenizer.decode(tokens[0], skip_special_tokens=True)
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return generated_code
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with gr.Blocks() as demo:
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gr.Markdown(title)
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gr.Markdown(description)
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with gr.Row():
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prompt = gr.Textbox(lines=2, placeholder="Enter your Python code prompt")
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output = gr.Textbox(label = "⚖️StableCode2")
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generate_button = gr.Button("Generate")
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generate_button.click(fn=generate_code, inputs=prompt, outputs=output)
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demo.launch()
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