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| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| import torch | |
| # Load the model and tokenizer | |
| model_path = 'Neo111x/falcon3-decompiler-3b-v1.5' # V1.5 Model | |
| tokenizer = AutoTokenizer.from_pretrained(model_path) | |
| model = AutoModelForCausalLM.from_pretrained(model_path, torch_dtype=torch.bfloat16) | |
| # Define the inference function | |
| def generate_response(input_text, temperature, top_k, top_p, progress=gr.Progress()): | |
| progress(0, "Processing input...") | |
| before = f"# This is the assembly code:\n"#prompt | |
| after = "\n# What is the source code?\n"#prompt | |
| input_func = before+input_text.strip()+after | |
| inputs = tokenizer(input_func, return_tensors="pt") | |
| progress(0.3, "Running inference...") | |
| outputs = model.generate( | |
| **inputs, | |
| max_length=512, # Adjust this if needed | |
| ) | |
| # do_sample=True, | |
| # top_k=int(top_k), | |
| # top_p=float(top_p), | |
| # temperature=float(temperature) | |
| progress(0.8, "Decoding response...") | |
| response = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| progress(1, "Done!") | |
| # Split the response into assembly and source code (if applicable) | |
| if "# This is the assembly code:" in response: | |
| parts = response.split("# What is the source code?") | |
| assembly_code = parts[0].replace("# This is the assembly code:", "").strip() | |
| source_code = parts[1].strip() if len(parts) > 1 else "" | |
| return f"```c\n{assembly_code}\n```", f"```c\n{source_code}\n```" | |
| else: | |
| return "No assembly code found.", "No source code found." | |
| # Create a Gradio interface with sliders | |
| interface = gr.Interface( | |
| fn=generate_response, | |
| inputs=[ | |
| gr.Textbox(lines=5, placeholder="Enter assembly code here...", label="Input Assembly Code"), | |
| gr.Slider(0.1, 2.0, value=0.7, step=0.1, label="Temperature"), | |
| gr.Slider(1, 100, value=50, step=1, label="Top-k"), | |
| gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-p") | |
| ], | |
| outputs=[ | |
| gr.Textbox(label="Assembly Code"), | |
| gr.Textbox(label="Source Code") | |
| ], | |
| title="Falcon decompiler Interactive Demo", | |
| description="Adjust the sliders for temperature, top-k, and top-p to customize the model's response." | |
| ) | |
| # Launch the Gradio app | |
| interface.launch() | |