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+FROM python:3.11-slim
+
+WORKDIR /app
+
+RUN apt-get update && apt-get install -y \
+    git \
+    git-lfs \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
+
+COPY requirements.txt .
+
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY app.py .
+
+EXPOSE 7860
+
+CMD ["python", "app.py"]

app.py

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+#!/usr/bin/env python3
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+import os
+
+# Model configuration
+MODEL_ID = "mx-llms/Lychee-GPT-9B"
+
+# Get HF token from environment
+HF_TOKEN = os.getenv("HF_TOKEN")
+
+print("🚀 Loading Lychee-GPT-9B model...")
+print("⏱️ This may take a few minutes...")
+
+try:
+    # Load tokenizer with token
+    tokenizer = AutoTokenizer.from_pretrained(
+        MODEL_ID, 
+        trust_remote_code=True,
+        token=HF_TOKEN
+    )
+    
+    # Load model with optimizations
+    model = AutoModelForCausalLM.from_pretrained(
+        MODEL_ID,
+        torch_dtype=torch.float32,
+        device_map="cpu",
+        trust_remote_code=True,
+        token=HF_TOKEN,
+    )
+    
+    model.eval()
+    print("✅ Model loaded successfully!")
+    
+except Exception as e:
+    print(f"❌ Error loading model: {e}")
+    print("\n⚠️ Make sure:")
+    print("1. Model is not gated OR")
+    print("2. HF_TOKEN environment variable is set")
+    model = None
+    tokenizer = None
+
+def generate_text(prompt, max_length=256, temperature=0.7, top_p=0.9):
+    """Generate text using Lychee-GPT-9B"""
+    if model is None or tokenizer is None:
+        return "❌ Model failed to load. Check that you have access to mx-llms/Lychee-GPT-9B model."
+    
+    try:
+        # Tokenize input
+        inputs = tokenizer(prompt, return_tensors="pt")
+        
+        # Generate with torch.no_grad for memory efficiency
+        with torch.no_grad():
+            output = model.generate(
+                inputs["input_ids"],
+                max_new_tokens=int(max_length),
+                temperature=float(temperature),
+                top_p=float(top_p),
+                do_sample=True,
+                pad_token_id=tokenizer.eos_token_id,
+            )
+        
+        # Decode output
+        response = tokenizer.decode(output[0], skip_special_tokens=True)
+        
+        # Remove input prompt from response
+        if prompt in response:
+            response = response.replace(prompt, "", 1).strip()
+        
+        return response if response else "No response generated"
+        
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
+
+# Create Gradio interface
+def create_interface():
+    with gr.Blocks(title="Lychee-GPT-9B", theme=gr.themes.Soft()) as demo:
+        gr.Markdown("""
+        # 🎉 Lychee-GPT-9B Demo
+        
+        আপনার নিজস্ব LLM Model!
+        
+        ⏱️ **নোট:** 
+        - প্রথম load: 2-3 মিনিট
+        - Response time: 30-90 সেকেন্ড (CPU তে)
+        """)
+        
+        with gr.Row():
+            with gr.Column(scale=1):
+                prompt = gr.Textbox(
+                    label="প্রশ্ন/Prompt",
+                    placeholder="কিছু লিখুন...",
+                    lines=4,
+                    info="আপনার প্রশ্ন বা prompt দিন"
+                )
+                
+                with gr.Row():
+                    max_len = gr.Slider(
+                        label="Max Length",
+                        minimum=10,
+                        maximum=512,
+                        value=256,
+                        step=10,
+                        info="Response এর সর্বোচ্চ length"
+                    )
+                
+                with gr.Row():
+                    temp = gr.Slider(
+                        label="Temperature",
+                        minimum=0.0,
+                        maximum=1.0,
+                        value=0.7,
+                        step=0.1,
+                        info="কম = সুসংগত, বেশি = সৃজনশীল"
+                    )
+                    
+                    top_p = gr.Slider(
+                        label="Top P",
+                        minimum=0.0,
+                        maximum=1.0,
+                        value=0.9,
+                        step=0.05,
+                        info="শব্দ নির্বাচন নিয়ন্ত্রণ"
+                    )
+                
+                submit_btn = gr.Button("🚀 Generate", variant="primary", size="lg")
+            
+            with gr.Column(scale=1):
+                output = gr.Textbox(
+                    label="Response",
+                    lines=10,
+                    interactive=False,
+                    info="Model এর response এখানে দেখা যাবে"
+                )
+        
+        # Examples
+        gr.Examples(
+            examples=[
+                ["বাংলা ভাষা সম্পর্কে বলুন"],
+                ["পাইথন প্রোগ্রামিং কি?"],
+                ["একটি সংক্ষিপ্ত গল্প বলুন"],
+                ["কৃত্রিম বুদ্ধিমত্তা কি?"],
+            ],
+            inputs=prompt,
+            label="উদাহরণ প্রশ্ন"
+        )
+        
+        # Connect button click
+        submit_btn.click(
+            fn=generate_text,
+            inputs=[prompt, max_len, temp, top_p],
+            outputs=output,
+            api_name="generate"
+        )
+        
+        # Allow Enter key
+        prompt.submit(
+            fn=generate_text,
+            inputs=[prompt, max_len, temp, top_p],
+            outputs=output,
+            api_name="generate"
+        )
+    
+    return demo
+
+if __name__ == "__main__":
+    demo = create_interface()
+    # Launch with share=True for HF Spaces (they handle public URL)
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=True,  # Important for Docker!
+        show_error=True,
+    )

requirements.txt

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+torch==2.12.1
+transformers==4.35.0
+accelerate>=0.29.0
+safetensors>=0.4.2
+gradio>=4.0