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| import gradio as gr | |
| from transformers import pipeline | |
| import torch | |
| 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"], | |
| ) | |
| instruct_pipeline = pipeline(model="databricks/dolly-v2-12b", torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto") | |
| def generate(instruction): | |
| return instruct_pipeline(instruction) | |
| 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?", | |
| "Write me a tweet about the launch of Dolly 2.0, a new LLM" | |
| ] | |
| def process_example(args): | |
| for x in generate(args): | |
| pass | |
| return x | |
| css = ".generating {visibility: hidden}" | |
| with gr.Blocks(theme=theme, analytics_enabled=False, css=css) as demo: | |
| with gr.Column(): | |
| gr.Markdown( | |
| """ ## Dolly 2.0 | |
| Dolly 2.0 is a 12B parameter language model based on the EleutherAI pythia model family and fine-tuned exclusively on a new, high-quality human generated instruction following dataset, crowdsourced among Databricks employees. For more details, please refer to the [model card](https://huggingface.co/databricks/dolly-v2-12b) | |
| 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=False, | |
| fn=process_example, | |
| outputs=[output], | |
| ) | |
| submit.click(generate, inputs=[instruction], outputs=[output]) | |
| instruction.submit(generate, inputs=[instruction], outputs=[output]) | |
| demo.queue(concurrency_count=16).launch(debug=True) | |