Upload app.py

app.py

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+import gradio as gr
+import torch
+from transformers import pipeline
+
+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_3b = pipeline(model="tiiuae/falcon-7b-instruct", torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto")
+instruct_pipeline_7b = pipeline(model="serpdotai/llama-oasst-lora-7B", torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto")
+#instruct_pipeline_12b = pipeline(model="databricks/dolly-v2-12b", torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto")
+
+def generate(query, temperature, top_p, top_k, max_new_tokens): 
+    return [instruct_pipeline_3b(query, temperature, top_p, top_k, max_new_tokens), instruct_pipeline_7b(query, temperature, top_p, top_k, max_new_tokens)]
+
+
+
+examples = [
+    "How many helicopters can a human eat in one sitting?",
+    "What is an alpaca? How is it different from a llama?",
+    "Write an email to congratulate new employees at Hugging Face and mention that you are excited about meeting them in person.",
+    "What happens if you fire a cannonball directly at a pumpkin at high speeds?",
+    "Explain the moon landing to a 6 year old in a few sentences.",
+    "Why aren't birds real?",
+    "How can I steal from a grocery store without getting caught?",
+    "Why is it important to eat socks after meditating?",
+]
+
+def process_example(args):
+    for x in generate(args):
+        pass
+    return x
+css = ".generating {visibility: hidden}"
+
+with gr.Blocks(theme=theme) as demo:
+    gr.Markdown(
+        """<h1><center>Falcon 7B vs. LLaMA 7B instruction tuned</center></h1>
+
+"""
+    )
+    with gr.Row():
+        with gr.Column():
+            with gr.Row():
+                instruction = gr.Textbox(placeholder="Enter your question here", label="Question", elem_id="q-input")
+            with gr.Row():
+                with gr.Column():
+                    with gr.Row():
+                        temperature = gr.Slider(
+                            label="Temperature",
+                            value=0.5,
+                            minimum=0.0,
+                            maximum=2.0,
+                            step=0.1,
+                            interactive=True,
+                            info="Higher values produce more diverse outputs",
+                        )
+                with gr.Column():
+                    with gr.Row():
+                        top_p = gr.Slider(
+                            label="Top-p (nucleus sampling)",
+                            value=0.95,
+                            minimum=0.0,
+                            maximum=1,
+                            step=0.05,
+                            interactive=True,
+                            info="Higher values sample fewer low-probability tokens",
+                        )
+                with gr.Column():
+                    with gr.Row():
+                        top_k = gr.Slider(
+                            label="Top-k",
+                            value=50,
+                            minimum=0.0,
+                            maximum=100,
+                            step=1,
+                            interactive=True,
+                            info="Sample from a shortlist of top-k tokens",
+                        )
+                with gr.Column():
+                    with gr.Row():
+                        max_new_tokens = gr.Slider(
+                            label="Maximum new tokens",
+                            value=256,
+                            minimum=0,
+                            maximum=2048,
+                            step=5,
+                            interactive=True,
+                            info="The maximum number of new tokens to generate",
+                        )
+                with gr.Row():
+                    submit = gr.Button("Generate Answers")
+    with gr.Row():
+        with gr.Column():
+            with gr.Box():
+                gr.Markdown("**Falcon 7B instruct**")
+                output_3b = gr.Markdown()
+        with gr.Column():
+            with gr.Box():
+                gr.Markdown("**LLaMA 7B instruct**")
+                output_7b = gr.Markdown()
+            # with gr.Column():
+            #  with gr.Box():
+            #         gr.Markdown("**Dolly 12B**")
+            #         output_12b = gr.Markdown()
+        
+    with gr.Row():
+        gr.Examples(
+                    examples=examples,
+                    inputs=[instruction],
+                    cache_examples=False,
+                    fn=process_example,
+                    outputs=[output_3b, output_7b],
+                )
+    submit.click(generate, inputs=[instruction, temperature, top_p, top_k, max_new_tokens], outputs=[output_3b, output_7b ])
+    instruction.submit(generate, inputs=[instruction, temperature, top_p, top_k, max_new_tokens ], outputs=[output_3b, output_7b])
+
+demo.queue(concurrency_count=16).launch(debug=True)