| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline | |
| import torch | |
| model_id = "TheBloke/MythoMax-L2-13B-GPTQ" | |
| tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=True) | |
| model = AutoModelForCausalLM.from_pretrained( | |
| model_id, | |
| device_map="auto", | |
| trust_remote_code=True, | |
| revision="main", | |
| torch_dtype=torch.float16, | |
| low_cpu_mem_usage=True | |
| ) | |
| pipe = pipeline("text-generation", model=model, tokenizer=tokenizer) | |
| def chat(prompt): | |
| output = pipe(prompt, max_new_tokens=400, temperature=0.7, top_p=0.9, repetition_penalty=1.1) | |
| return output[0]["generated_text"] | |
| gr.Interface(fn=chat, | |
| inputs=gr.Textbox(label="Prompt", lines=6, placeholder="Tulis kode atau pertanyaan..."), | |
| outputs=gr.Textbox(label="Respon MythoMax"), | |
| title="🧙♂️ MythoMax L2 13B Coder", | |
| description="Model LLM roleplay + coding kelas berat 🤘 oleh King Hammz" | |
| ).launch() |