# Copyright (c) ModelScope Contributors. All rights reserved. import gradio as gr from typing import Type from ..base import BaseUI class Sample(BaseUI): group = 'llm_sample' locale_dict = { 'sampler_type': { 'label': { 'zh': '采样类型', 'en': 'Sampler type' }, }, 'sampler_engine': { 'label': { 'zh': '推理引擎', 'en': 'Infer engine' }, }, 'num_return_sequences': { 'label': { 'zh': '采样返回的原始序列数量', 'en': 'Num of original sequences returned by sampling' }, }, 'n_best_to_keep': { 'label': { 'zh': '最佳序列数量', 'en': 'Num of best sequences' }, }, 'max_new_tokens': { 'label': { 'zh': '生成序列最大长度', 'en': 'Max new tokens' }, }, 'temperature': { 'label': { 'zh': '采样温度', 'en': 'Temperature' }, }, 'top_k': { 'label': { 'zh': 'Top-k', 'en': 'Top-k' }, }, 'top_p': { 'label': { 'zh': 'Top-p', 'en': 'Top-p' }, }, 'repetition_penalty': { 'label': { 'zh': '重复惩罚', 'en': 'Repetition Penalty' }, }, } @classmethod def do_build_ui(cls, base_tab: Type['BaseUI']): with gr.Row(): gr.Dropdown(elem_id='sampler_type', choices=['sample', 'distill'], value='sample', scale=5) gr.Dropdown( elem_id='sampler_engine', choices=['transformers', 'lmdeploy', 'vllm', 'no', 'client'], value='transformers', scale=5) gr.Slider(elem_id='num_return_sequences', minimum=1, maximum=128, step=1, value=64, scale=5) gr.Slider(elem_id='n_best_to_keep', minimum=1, maximum=64, step=1, value=5, scale=5) with gr.Row(): gr.Textbox(elem_id='max_new_tokens', lines=1, value='2048') gr.Slider(elem_id='temperature', minimum=0.0, maximum=10, step=0.1, value=1.0) gr.Slider(elem_id='top_k', minimum=1, maximum=100, step=5, value=20) gr.Slider(elem_id='top_p', minimum=0.0, maximum=1.0, step=0.05, value=0.7) gr.Slider(elem_id='repetition_penalty', minimum=0.0, maximum=10, step=0.05, value=1.05)