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README.md

@@ -1,13 +1,17 @@
----
-title: Demo Gpt2
-emoji: 🏆
-colorFrom: yellow
-colorTo: gray
-sdk: gradio
-sdk_version: 4.28.3
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+#### Name:
+**Zishi Zhang**
+
+******
+
+### Student ID:
+**23-741-390**
+
+******
+
+### Collaborators:
+**Yuhao Fan**
+
+******
+
+### URL:
+**<https://huggingface.co/spaces/CedricZ/demo_gpt2>**

final_app.py

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+import gradio as gr
+from transformers import pipeline, GenerationConfig 
+
+#Load pipeline
+generator = pipeline("text-generation", model="gpt2")
+config = GenerationConfig.from_pretrained("gpt2")
+
+def greet(prompt, temperature, max_lenth, top_p, samples):
+    #Enable greedy decoding if temperature is 0
+    config.do_sample = True if temperature != 0 else False
+
+    #Takes temperature and top_p value
+    config.temperature = temperature
+    config.top_p = top_p
+
+    #Samples
+    sample_input = {'Sample 1': 'Hi, this is a demo prompt for you',
+                    'Sample 2': 'Alber Einstein is a famous physicist graduated from',
+                    'Sample 3': 'University of Zurich located in'}
+    
+    #Choose between samples
+    if samples and prompt == '':
+        prompt = sample_input[samples]
+
+    #Streaming the output
+    for i in range(max_lenth):
+        a = generator(prompt, max_new_tokens=1, generation_config=config)
+        prompt=a[0]['generated_text']
+        yield a[0]['generated_text']
+
+demo = gr.Interface(
+    fn=greet,
+    inputs=[gr.Textbox(placeholder = "Write a tagline for an ice cream shop.", label="prompt", lines=5),
+            gr.Slider(value=1, minimum=0, maximum=2, label='temperature',
+                      info='''Temperature controls the randomness of the text generation.
+                      1.0 makes the model more likely to generate diverse and sometimes more unexpected outputs.
+                      0.0 makes the model's responses more deterministic and predictable.'''),
+            gr.Slider(value=16, minimum=1, maximum=256, step=1, label='max_lenth',
+                      info='''Maximum number of tokens that the model will generate in the output.'''),
+            gr.Slider(value=1, minimum=0, maximum=1, label='top_p',
+                      info='''Top-p controls the model's focus during text generation. 
+                      It allows only the most probable tokens to be considered for generation, where the cumulative probability of these tokens must exceed this value.'''),
+            gr.Dropdown(['Sample 1', 'Sample 2', 'Sample 3'], label="Sample Prompts",
+                        info='''Some sample Prompts for you!''')],
+    outputs=[gr.Textbox(label='Output texts')],
+)
+
+demo.launch()

mockup.py

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+import gradio as gr
+
+def greet(prompt, temperature, max_lenth, top_p):
+    return "Hello, world!"
+
+demo = gr.Interface(
+    fn=greet,
+    inputs=["text", "slider", "slider", "slider"],
+    outputs=["text"],
+)
+
+demo.launch()

mockup_v2.py

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+import gradio as gr
+
+def greet(prompt, temperature, max_lenth, top_p):
+    return f"Hello, world! {temperature}"
+
+demo = gr.Interface(
+    fn=greet,
+    inputs=[gr.Textbox(placeholder = "Write a tagline for an ice cream shop.", label="prompt", lines=5),
+            gr.Slider(value=1, minimum=0, maximum=2, label='temperature',
+                      info='''Temperature controls the randomness of the text generation.
+                      1.0 makes the model more likely to generate diverse and sometimes more unexpected outputs.
+                      0.0 makes the model's responses more deterministic and predictable.'''),
+            gr.Slider(value=16, minimum=1, maximum=256, step=1, label='max_lenth',
+                      info='''Maximum number of tokens that the model will generate in the output.'''),
+            gr.Slider(value=1, minimum=0, maximum=1, label='top_p',
+                      info='''Top-p controls the model's focus during text generation. 
+                      It allows only the most probable tokens to be considered for generation, where the cumulative probability of these tokens must exceed this value.''')
+            ],
+    outputs=[gr.Textbox(label='Output texts')],
+)
+
+demo.launch()