Add demo

.pre-commit-config.yaml

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+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.3.0
+    hooks:
+    - id: trailing-whitespace
+    - id: requirements-txt-fixer
+
+  - repo: https://github.com/PyCQA/flake8
+    rev: 6.0.0
+    hooks:
+    - id: flake8
+      args: [
+        # E501: line too long
+        "--ignore", "E501",
+        # "--max-line-length", "120",
+      ]
+
+  - repo: https://github.com/psf/black
+    rev: 22.12.0
+    hooks:
+    - id: black
+
+  - repo: https://github.com/pycqa/isort
+    rev: 5.11.4
+    hooks:
+      - id: isort
+        name: isort (python)

app.py

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+# from transformers import AutoTokenizer, AutoModelForCausalLM
+import gradio as gr
+import torch
+from transformers import AutoModelForCausalLM
+from transformers import AutoTokenizer
+
+target_text = """\
+Obama was born in Honolulu, Hawaii.
+After graduating from Columbia University in 1983, he worked as a community organizer in Chicago.
+In 1988, he enrolled in Harvard Law School, where he was the first black president of the Harvard Law Review.
+After graduating, he became a civil rights attorney and an academic, teaching constitutional law at the University of Chicago Law School from 1992 to 2004.
+Turning to elective politics, he represented the 13th district in the Illinois Senate from 1997 until 2004, when he ran for the U.S.
+Senate.
+Obama received national attention in 2004 with his March Senate primary win, his well-received July Democratic National Convention keynote address, and his landslide November election to the Senate.
+In 2008, after a close primary campaign against Hillary Clinton, he was nominated by the Democratic Party for president and chose Joe Biden as his running mate.
+Obama was elected over Republican nominee John McCain in the presidential election and was inaugurated on January 20, 2009.
+Nine months later, he was named the 2009 Nobel Peace Prize laureate, a decision that drew a mixture of praise and criticism.
+"""
+
+
+tokenizer = AutoTokenizer.from_pretrained("gpt2")
+model = AutoModelForCausalLM.from_pretrained("gpt2")
+model.eval()
+
+
+def get_next_word(text: str) -> str:
+    inputs = tokenizer(text, return_tensors="pt")
+    with torch.no_grad():
+        logits = model(**inputs).logits
+
+    last_token = logits[0, -1]
+    top_3 = torch.topk(last_token, 3)
+    input_ids = list(inputs.input_ids.squeeze())
+    argmax = top_3.indices[0]
+    input_ids.append(argmax)
+    return "!!!", tokenizer.decode(input_ids)
+
+
+def build_demo():
+    with gr.Blocks() as demo:
+        gr.Markdown("<h1><center>Can you beat a language model?</center></h1>")
+
+        with gr.Row():
+            prompt_text = gr.Markdown(target_text)
+        with gr.Row():
+            with gr.Column():
+                guess = gr.Textbox(label="Guess!")
+                guess_btn = gr.Button(value="Guess!")
+            with gr.Column():
+                lm_guess = gr.Textbox(label="LM guess")
+
+        guess_btn.click(get_next_word, inputs=guess, outputs=[prompt_text, lm_guess], api_name="get_next_word")
+        # examples = gr.Examples(
+        #     examples=["I went to the supermarket yesterday.", "Helen is a good swimmer."], inputs=[guess]
+        # )
+
+    return demo
+
+
+def wip_sign():
+    with gr.Blocks() as demo:
+        gr.Markdown("<h1><center>Can you beat a language model?</center></h1>")
+        with gr.Row():
+            gr.Markdown("<h1><center>⛔👷‍♂️ Work in progress, come back later </center></h1>")
+
+    return demo
+
+
+def main():
+    # demo = build_demo()
+    demo = wip_sign()
+    demo.launch(debug=True)
+
+
+if __name__ == "__main__":
+    main()

pyproject.toml

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+[tool.black]
+line-length = 120
+
+[tool.isort]
+atomic = true
+profile = "black"
+line_length = 120
+force_single_line = true
+known_first_party = ["black"]

requirements.txt

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+gradio==3.16.2
+torch==1.13.1
+transformers==4.25.1