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Update app.py
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app.py
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import gradio as gr
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import os
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from transformers import GemmaTokenizer, AutoModelForCausalLM
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# Set an environment variable
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HF_TOKEN = os.environ.get("HF_TOKEN", None)
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tokenizer = GemmaTokenizer.from_pretrained("google/codegemma-7b-it")
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model = AutoModelForCausalLM.from_pretrained("google/codegemma-7b-it").to("cuda:0")
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placeholder = """
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<img src="https://huggingface.co/spaces/ysharma/CodeGemma/resolve/main/gemma_lockup_vertical_full-color_rgb.png" style="width:40%">
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<b>CodeGemma-7B-IT</b>
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"""
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with gr.Blocks(fill_height=True) as demo:
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if __name__ == "__main__":
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demo.launch(debug=False)
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import gradio as gr
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import os
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import spaces
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from transformers import GemmaTokenizer, AutoModelForCausalLM
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# Set an environment variable
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HF_TOKEN = os.environ.get("HF_TOKEN", None)
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# Load the tokenizer and model
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tokenizer = GemmaTokenizer.from_pretrained("google/codegemma-7b-it")
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model = AutoModelForCausalLM.from_pretrained("google/codegemma-7b-it").to("cuda:0")
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def codegemma(message: str, history: list, temperature: float, max_new_tokens: int) -> str:
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"""
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Generate a response using the CodeGemma model.
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Args:
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message (str): The input message.
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history (list): The conversation history used by ChatInterface.
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temperature (float): The temperature for generating the response.
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max_new_tokens (int): The maximum number of new tokens to generate.
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Returns:
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str: The generated response.
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"""
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input_ids = tokenizer(message, return_tensors="pt")
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outputs = model.generate(
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**input_ids,
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temperature=temperature,
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max_new_tokens=max_new_tokens,
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)
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response = tokenizer.decode(outputs[0])
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return response
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placeholder = """
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<img src="https://huggingface.co/spaces/ysharma/CodeGemma/resolve/main/gemma_lockup_vertical_full-color_rgb.png" style="width:40%">
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<b>CodeGemma-7B-IT</b>
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"""
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# Gradio block
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with gr.Blocks(fill_height=True) as demo:
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gr.Markdown("# GEMMA-7b-IT")
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#with gr.Tab('CodeGemma Chatbot'):
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gr.ChatInterface(codegemma,
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examples=[["Write a Python function to calculate the nth fibonacci number."]],
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fill_height=True,
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additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False),
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additional_inputs=[
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gr.Slider(0, 1, 0.95, label="Temperature", render=False),
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gr.Slider(128, 4096, 512, label="Max new tokens", render=False ),
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],
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)
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if __name__ == "__main__":
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demo.launch(debug=False)
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