feat: create demo app

.gitmodules

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+[submodule "RetNet"]
+	path = RetNet
+	url = https://github.com/syncdoth/RetNet.git

README.md

@@ -1,12 +1,12 @@
 ---
 title: LightNovel Intro RetNet 400M Demo
-emoji: 🌍
+emoji: 🖋️
 colorFrom: gray
-colorTo: red
+colorTo: blue
 sdk: gradio
 sdk_version: 3.47.1
 app_file: app.py
-pinned: false
+pinned: true
 license: mit
 ---
 

RetNet

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+Subproject commit a4253a7bc16519459320c140a7e3d14b5f017b32

app.py

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+import torch
+
+from RetNet.retnet.modeling_retnet import RetNetForCausalLM
+from transformers import AutoTokenizer
+
+import gradio as gr
+
+MODEL_NAME = "p1atdev/LightNovel-Intro-RetNet-400M"
+
+DEFAULT_INPUT_TEXT = "目が覚めると、"
+
+EXAMPLE_INPUTS = [
+    DEFAULT_INPUT_TEXT,
+    "冒険者ギルドには",
+    "真っ白い部屋の中、そこには",
+    "20XX年、",
+    "「なんだって!?」",
+    "どうやらトラックにはねられ、俺は",
+]
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = RetNetForCausalLM.from_pretrained(MODEL_NAME)
+model.eval()
+
+
+@torch.no_grad()
+def generate(
+    input_text,
+    max_new_tokens=128,
+    do_sample=True,
+    temperature=1.0,
+    top_p=0.95,
+    top_k=20,
+):
+    if input_text.strip() == "":
+        return ""
+
+    inputs = tokenizer(input_text, return_tensors="pt", add_special_tokens=False)
+    generated = model.custom_generate(
+        **inputs,
+        parallel_compute_prompt=True,
+        max_new_tokens=max_new_tokens,
+        do_sample=do_sample,
+        temperature=temperature,
+        top_p=top_p,
+        top_k=top_k,
+    )
+    return tokenizer.batch_decode(generated)[0]
+
+
+def continue_generate(
+    input_text,
+    *args,
+):
+    return input_text, generate(input_text, *args)
+
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+        """\
+# LightNovel-Intro-RetNet-400M-Demo
+
+ライトノベルの冒頭だけを学習した 400M パラメータの RetNet モデルのデモです。
+
+### 参考:
+
+- https://github.com/syncdoth/RetNet
+"""
+    )
+
+    input_text = gr.Textbox(
+        value=DEFAULT_INPUT_TEXT,
+        placeholder="私の名前は...",
+        lines=2,
+    )
+    output_text = gr.Textbox(
+        value="",
+        placeholder="ここに出力が表示されます...",
+        lines=8,
+        interactive=False,
+    )
+
+    with gr.Row():
+        generate_btn = gr.Button("Generate ✒️", variant="primary")
+        continue_btn = gr.Button("Continue ➡️", variant="secondary")
+        clear_btn = gr.ClearButton(
+            value="Clear 🧹",
+            components=[input_text, output_text],
+        )
+
+    with gr.Accordion("Advanced settings", open=False):
+        max_tokens = gr.Slider(
+            label="Max tokens",
+            minimum=8,
+            maximum=512,
+            value=128,
+            step=4,
+        )
+        do_sample = gr.Checkbox(
+            label="Do sample",
+            value=True,
+        )
+        temperature = gr.Slider(
+            label="Temperature",
+            minimum=0,
+            maximum=2,
+            value=1,
+            step=0.05,
+        )
+        top_p = gr.Slider(
+            label="Top p",
+            minimum=0,
+            maximum=1,
+            value=0.95,
+            step=0.05,
+        )
+        top_k = gr.Slider(
+            label="Top k",
+            minimum=0,
+            maximum=100,
+            value=20,
+            step=1,
+        )
+
+    gr.Examples(
+        examples=EXAMPLE_INPUTS,
+        inputs=input_text,
+    )
+
+    generate_btn.click(
+        fn=generate,
+        inputs=[
+            input_text,
+            max_tokens,
+            do_sample,
+            temperature,
+            top_p,
+            top_k,
+        ],
+        outputs=output_text,
+        queue=False,
+    )
+    continue_btn.click(
+        fn=continue_generate,
+        inputs=[
+            input_text,
+            max_tokens,
+            do_sample,
+            temperature,
+            top_p,
+            top_k,
+        ],
+        outputs=[input_text, output_text],
+        queue=False,
+    )
+
+demo.launch()

requirements.txt

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+transformers==4.34.0