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| import gradio as gr | |
| from transformers import pipeline | |
| import torch | |
| import subprocess | |
| import spaces | |
| import os | |
| # Initialize the model pipeline | |
| generator = pipeline('text-generation', model='Locutusque/ChatHercules-2.5-Mistral-7B-DPO', torch_dtype=torch.bfloat16, token=os.environ["HF"]) | |
| def generate_text(prompt, temperature, top_p, top_k, repetition_penalty, max_length): | |
| # Generate text using the model | |
| generator.model.cuda() | |
| generator.device = torch.device("cuda") | |
| prompt = f"<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n" | |
| outputs = generator( | |
| prompt, | |
| do_sample=True, | |
| max_new_tokens=max_length, | |
| temperature=temperature, | |
| top_p=top_p, | |
| top_k=top_k, | |
| repetition_penalty=repetition_penalty, | |
| return_full_text=False | |
| ) | |
| # Extract the generated text and return it | |
| generated_text = outputs[0]['generated_text'] | |
| return generated_text | |
| # Create the Gradio interface | |
| iface = gr.Interface( | |
| fn=generate_text, | |
| inputs=[ | |
| gr.Textbox(label="Prompt", lines=2, placeholder="Type a prompt..."), | |
| gr.Slider(minimum=0.1, maximum=2.0, step=0.01, value=0.8, label="Temperature"), | |
| gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.95, label="Top p"), | |
| gr.Slider(minimum=0, maximum=100, step=1, value=40, label="Top k"), | |
| gr.Slider(minimum=1.0, maximum=2.0, step=0.01, value=1.10, label="Repetition Penalty"), | |
| gr.Slider(minimum=5, maximum=4096, step=5, value=1024, label="Max Length") | |
| ], | |
| outputs=gr.Textbox(label="Generated Text"), | |
| title="ChatHercules-2.5-Mistral-7B", | |
| description="Try out the ChatHercules-2.5-Mistral-7B model for free!" | |
| ) | |
| iface.launch() |