| import gradio as gr | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| model_name = "TheBloke/MythoMax-L2-13B-GGUF" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForCausalLM.from_pretrained(model_name) | |
| def chat(input_text): | |
| inputs = tokenizer(input_text, return_tensors="pt") | |
| output = model.generate(**inputs, max_new_tokens=100) | |
| response = tokenizer.decode(output[0], skip_special_tokens=True) | |
| return response | |
| iface = gr.Interface( | |
| fn=chat, | |
| inputs="text", | |
| outputs="text", | |
| title="Dika AI - MythoMax Lite", | |
| description="Chatbot AI berbasis MythoMax 13B GGUF, optimized for Hugging Face free tier!" | |
| ) | |
| iface.launch() | |