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| from __future__ import annotations | |
| import gradio as gr | |
| import time | |
| from ctransformers import AutoModelForCausalLM | |
| from typing import Iterable | |
| import gradio as gr | |
| from gradio.themes.base import Base | |
| from gradio.themes.utils import colors, fonts, sizes | |
| import subprocess | |
| from huggingface_hub import hf_hub_download | |
| # Set gpu_layers to the number of layers to offload to GPU. Set to 0 if no GPU acceleration is available on your system. | |
| model = AutoModelForCausalLM.from_pretrained("TheBloke/Mistral-7B-Instruct-v0.1-GGUF", model_file="mistral-7b-instruct-v0.1.Q5_K_S.gguf", model_type="mistral", gpu_layers=0) | |
| ins = '''[INST] <<FRIDAY>> | |
| You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. | |
| If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. | |
| <</FRIDAY>> | |
| {} [/INST] | |
| ''' | |
| theme = gr.themes.Monochrome( | |
| primary_hue="indigo", | |
| secondary_hue="blue", | |
| neutral_hue="slate", | |
| radius_size=gr.themes.sizes.radius_sm, | |
| font=[gr.themes.GoogleFont("Open Sans"), "ui-sans-serif", "system-ui", "sans-serif"], | |
| ) | |
| def response(question): | |
| res = model(ins.format(question)) | |
| yield res | |
| examples = [ | |
| "Instead of making a peanut butter and jelly sandwich, what else could I combine peanut butter with in a sandwich? Give five ideas", | |
| "How do I make a campfire?", | |
| "Explain to me the difference between nuclear fission and fusion.", | |
| "I'm selling my Nikon D-750, write a short blurb for my ad." | |
| ] | |
| def process_example(args): | |
| for x in response(args): | |
| pass | |
| return x | |
| css = ".generating {visibility: hidden}" | |
| # Based on the gradio theming guide and borrowed from https://huggingface.co/spaces/shivi/dolly-v2-demo | |
| class SeafoamCustom(Base): | |
| def __init__( | |
| self, | |
| *, | |
| primary_hue: colors.Color | str = colors.emerald, | |
| secondary_hue: colors.Color | str = colors.blue, | |
| neutral_hue: colors.Color | str = colors.blue, | |
| spacing_size: sizes.Size | str = sizes.spacing_md, | |
| radius_size: sizes.Size | str = sizes.radius_md, | |
| font: fonts.Font | |
| | str | |
| | Iterable[fonts.Font | str] = ( | |
| fonts.GoogleFont("Quicksand"), | |
| "ui-sans-serif", | |
| "sans-serif", | |
| ), | |
| font_mono: fonts.Font | |
| | str | |
| | Iterable[fonts.Font | str] = ( | |
| fonts.GoogleFont("IBM Plex Mono"), | |
| "ui-monospace", | |
| "monospace", | |
| ), | |
| ): | |
| super().__init__( | |
| primary_hue=primary_hue, | |
| secondary_hue=secondary_hue, | |
| neutral_hue=neutral_hue, | |
| spacing_size=spacing_size, | |
| radius_size=radius_size, | |
| font=font, | |
| font_mono=font_mono, | |
| ) | |
| super().set( | |
| button_primary_background_fill="linear-gradient(90deg, *primary_300, *secondary_400)", | |
| button_primary_background_fill_hover="linear-gradient(90deg, *primary_200, *secondary_300)", | |
| button_primary_text_color="white", | |
| button_primary_background_fill_dark="linear-gradient(90deg, *primary_600, *secondary_800)", | |
| block_shadow="*shadow_drop_lg", | |
| button_shadow="*shadow_drop_lg", | |
| input_background_fill="zinc", | |
| input_border_color="*secondary_300", | |
| input_shadow="*shadow_drop", | |
| input_shadow_focus="*shadow_drop_lg", | |
| ) | |
| seafoam = SeafoamCustom() | |
| with gr.Blocks(theme=seafoam, analytics_enabled=False, css=css) as demo: | |
| with gr.Column(): | |
| gr.Markdown( | |
| """ ## Mistral-7b | |
| Type in the box below and click the button to generate answers to your most pressing questions! | |
| """ | |
| ) | |
| with gr.Row(): | |
| with gr.Column(scale=3): | |
| instruction = gr.Textbox(placeholder="Enter your question here", label="Question", elem_id="q-input") | |
| with gr.Box(): | |
| gr.Markdown("**Answer**") | |
| output = gr.Markdown(elem_id="q-output") | |
| submit = gr.Button("Generate", variant="primary") | |
| gr.Examples( | |
| examples=examples, | |
| inputs=[instruction], | |
| cache_examples=True, | |
| fn=process_example, | |
| outputs=[output], | |
| ) | |
| submit.click(response, inputs=[instruction], outputs=[output]) | |
| instruction.submit(response, inputs=[instruction], outputs=[output]) | |
| demo.queue(concurrency_count=1).launch(debug=False,share=True) |