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Browse files- app.py +64 -0
- requirements.txt +1 -0
app.py
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import os
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import urllib.request
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import gradio as gr
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from llama_cpp import Llama
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def download_file(file_link, filename):
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# Checks if the file already exists before downloading
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if not os.path.isfile(filename):
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urllib.request.urlretrieve(file_link, filename)
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print("File downloaded successfully.")
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else:
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print("File already exists.")
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# Dowloading GGML model from HuggingFace
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ggml_model_path = "https://huggingface.co/TheBloke/Starling-LM-7B-alpha-GGUF/resolve/main/starling-lm-7b-alpha.Q4_K_S.gguf"
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filename = "starling-lm-7b-alpha.Q4_K_S.gguf"
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download_file(ggml_model_path, filename)
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llm = Llama(model_path=filename, n_ctx=512, n_batch=126)
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def create_prompt(text):
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prompt = f"""GPT4 Correct User: {text}<|end_of_turn|>GPT4 Correct Assistant:"""
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return prompt
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def generate_text(prompt="Who is the CEO of Apple?"):
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input_text = create_prompt(prompt)
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output = llm(
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input_text,
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max_tokens=256,
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temperature=0.1,
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top_p=0.5,
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echo=False,
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stop=["#"],
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)
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output_text = output["choices"][0]["text"].strip()
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# Remove Prompt Echo from Generated Text
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cleaned_output_text = output_text.replace(prompt, "")
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return cleaned_output_text
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description = "Starling-7B GGUF"
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examples = [
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["What is the capital of France?", "The capital of France is Paris."],
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[
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"Who wrote the novel 'Pride and Prejudice'?",
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"The novel 'Pride and Prejudice' was written by Jane Austen.",
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],
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["What is the square root of 64?", "The square root of 64 is 8."],
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]
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gradio_interface = gr.Interface(
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fn=generate_text,
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inputs="text",
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outputs="text",
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examples=examples,
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title="Starling-7B GGUF",
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)
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gradio_interface.launch()
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requirements.txt
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llama-cpp-python==0.2.33
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