feat: init

app.py

@@ -0,0 +1,62 @@
+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)

requirements.txt

@@ -0,0 +1,4 @@
+transformers
+torch
+accelerate
+gradio