[update]add code

.gitignore

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+
+.git/
+.idea/
+
+**/flagged/
+**/__pycache__/

README.md

@@ -1,13 +1,12 @@
 ---
-title: Gpt2 Chat
-emoji: 📊
-colorFrom: green
-colorTo: blue
+title: GPT2 Chat
+emoji: 🐠
+colorFrom: purple
+colorTo: green
 sdk: gradio
-sdk_version: 3.50.2
-app_file: app.py
+sdk_version: 3.41.2
+app_file: main.py
 pinned: false
-license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

main.py

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+#!/usr/bin/python3
+# -*- coding: utf-8 -*-
+import argparse
+from collections import defaultdict
+import os
+
+import gradio as gr
+from threading import Thread
+from transformers.models.gpt2.modeling_gpt2 import GPT2LMHeadModel
+from transformers.models.bert.tokenization_bert import BertTokenizer
+from transformers.generation.streamers import TextIteratorStreamer
+import torch
+
+from project_settings import project_path
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("--max_new_tokens", default=512, type=int)
+    parser.add_argument("--top_p", default=0.9, type=float)
+    parser.add_argument("--temperature", default=0.35, type=float)
+    parser.add_argument("--repetition_penalty", default=1.0, type=float)
+    parser.add_argument('--device', default="cuda" if torch.cuda.is_available() else "cpu", type=str)
+
+    args = parser.parse_args()
+    return args
+
+
+description = """
+## GPT2 Chat
+"""
+
+
+examples = [
+
+]
+
+
+def main():
+    args = get_args()
+
+    if args.device == 'auto':
+        device = 'cuda' if torch.cuda.is_available() else 'cpu'
+    else:
+        device = args.device
+
+    input_text_box = gr.Text(label="text")
+    output_text_box = gr.Text(lines=4, label="generated_content")
+
+    def fn_stream(text: str,
+                  max_new_tokens: int = 200,
+                  top_p: float = 0.85,
+                  temperature: float = 0.35,
+                  repetition_penalty: float = 1.2,
+                  model_name: str = "qgyd2021/lib_service_4chan",
+                  is_chat: bool = True,
+                  ):
+        tokenizer = BertTokenizer.from_pretrained(model_name)
+        model = GPT2LMHeadModel.from_pretrained(model_name)
+        model = model.eval()
+
+        text_encoded = tokenizer.__call__(text, add_special_tokens=False)
+        input_ids_ = text_encoded["input_ids"]
+
+        input_ids = [tokenizer.cls_token_id]
+        input_ids.extend(input_ids_)
+        if is_chat:
+            input_ids.append(tokenizer.sep_token_id)
+
+        input_ids = torch.tensor([input_ids], dtype=torch.long)
+        input_ids = input_ids.to(device)
+
+        output = ""
+        streamer = TextIteratorStreamer(tokenizer=tokenizer)
+
+        generation_kwargs = dict(
+            inputs=input_ids,
+            max_new_tokens=max_new_tokens,
+            do_sample=True,
+            top_p=top_p,
+            temperature=temperature,
+            repetition_penalty=repetition_penalty,
+            eos_token_id=tokenizer.sep_token_id if is_chat else None,
+            pad_token_id=tokenizer.pad_token_id,
+            streamer=streamer,
+        )
+        thread = Thread(target=model.generate, kwargs=generation_kwargs)
+        thread.start()
+
+        for output_ in streamer:
+            output_ = output_.replace(" ", "")
+            output_ = output_.replace("[CLS]", "")
+            output_ = output_.replace("[SEP]", "\n")
+            output_ = output_.replace("[UNK]", "")
+
+            output += output_
+            output_text_box.value += output
+            yield output
+
+    demo = gr.Interface(
+        fn=fn_stream,
+        inputs=[
+            input_text_box,
+            gr.Slider(minimum=0, maximum=512, value=512, step=1, label="max_new_tokens"),
+            gr.Slider(minimum=0, maximum=1, value=0.85, step=0.01, label="top_p"),
+            gr.Slider(minimum=0, maximum=1, value=0.35, step=0.01, label="temperature"),
+            gr.Slider(minimum=0, maximum=2, value=1.2, step=0.01, label="repetition_penalty"),
+            gr.Dropdown(choices=["qgyd2021/lib_service_4chan"], label="model_name"),
+            gr.Checkbox(label="is_chat")
+        ],
+        outputs=[output_text_box],
+        examples=[
+            ["怎样擦屁股才能擦的干净", 512, 0.75, 0.35, 1.2, "qgyd2021/lib_service_4chan", True],
+        ],
+        cache_examples=False,
+        examples_per_page=50,
+        title="H Novel Generate",
+        description=description,
+    )
+    demo.queue().launch()
+
+    return
+
+
+if __name__ == '__main__':
+    main()

project_settings.py

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+#!/usr/bin/python3
+# -*- coding: utf-8 -*-
+import os
+from pathlib import Path
+
+
+project_path = os.path.abspath(os.path.dirname(__file__))
+project_path = Path(project_path)
+
+
+if __name__ == '__main__':
+    pass

requirements.txt

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+gradio==3.41.2
+pydantic==1.10.12
+thinc==7.4.6
+spacy==2.3.9
+transformers==4.30.2
+numpy==1.21.4
+tqdm==4.62.3
+torch==1.13.0
+datasets