Super-squash branch 'main' using huggingface_hub

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README.md

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+---
+title: Prompt Enhancer Mini
+short_description: Enhance text-to-image prompts with finetuned Gemma3-270M
+colorFrom: blue
+colorTo: red
+sdk: gradio
+sdk_version: 5.49.1
+app_file: app.py
+pinned: false
+license: cc-by-4.0
+emoji: ⚡
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import os
+import gradio as gr
+
+from threading import Thread
+
+from transformers import AutoTokenizer, AutoModelForCausalLM, TextIteratorStreamer
+
+hf_token = os.environ.get("HF_TOKEN")
+
+model = AutoModelForCausalLM.from_pretrained("shb777/PromptTuner-exp1", token=hf_token)
+tokenizer = AutoTokenizer.from_pretrained("shb777/PromptTuner-exp1")
+model.eval()
+
+def enhance_prompt(user_prompt: str):
+    messages = [
+        {"role": "system", "content": "Enhance Prompt"},
+        {"role": "user", "content": user_prompt}
+    ]
+    prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    inputs = tokenizer(prompt, return_tensors="pt")
+    streamer = TextIteratorStreamer(tokenizer, skip_special_tokens=True, skip_prompt=True)
+    generation_kwargs = dict(inputs, 
+        max_new_tokens=512, 
+        streamer=streamer, 
+        do_sample=True,
+        temperature = 1, 
+        top_p = 0.95, 
+        top_k = 64
+    )
+
+    yield "", gr.update(interactive=False), gr.update(interactive=False)
+
+    thread = Thread(target=model.generate, kwargs=generation_kwargs)
+    thread.start()
+
+    output = ""
+    for text in streamer:
+        output += text
+        yield output, gr.update(), gr.update()
+
+    yield output, gr.update(interactive=True), gr.update(interactive=True)
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Prompt Enhancer")
+
+    with gr.Row():
+        with gr.Column():
+            input_text = gr.Textbox(
+                label="Your Prompt",
+                lines=3,
+                scale=4
+            )
+            with gr.Row():
+                enhance_btn = gr.Button("Enhance", variant="primary", scale=1)
+                clear_btn = gr.Button("Clear", variant="primary", scale=1)
+
+        with gr.Column():
+            output = gr.Textbox(label="Enhanced Prompt", lines=6, show_copy_button=True)
+
+    with gr.Row():
+        gr.Examples(
+            examples=[
+                ["fox, red tail, blue moon, clouds"], 
+                ["room with french window, cozy morning vibes, minimal"], 
+                ["anime style, sunset, japan"]
+            ],
+            inputs=input_text,
+            label="Examples",
+        )
+
+    enhance_btn.click(fn=enhance_prompt, inputs=input_text, outputs=[output, enhance_btn, clear_btn])
+    clear_btn.click(fn=lambda: ("", ""), inputs=None, outputs=[input_text, output])
+
+if __name__ == "__main__":
+    demo.queue(max_size=10, default_concurrency_limit=1).launch(mcp_server=True, show_api=False, ssr_mode=False)

requirements.txt

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+gradio
+transformers
+torch
+accelerate
+peft