pip install modelscope_studio02使用案例import gradio as grimport modelscope_studio.components.antd as antdimport antd.Icon("GithubOutlined")组件上下文联动在modelscope-studio中,也支持不同组件之间的联动效果,以常见的表单提交场景为例:import gradio as grimport import gradio as grimport modelscope_studio.components.antd as antdimport modelscope_studio.components.base
import gradio as grimport numpy as npimport tcvectordbfrom tcvectordb.model.collection import Embeddingfrom 为了实现交互界面的功能,我们需要在一个新的py文件中编写以下代码:import gradio as grimport tcvectordbfrom tcvectordb.model.document import
: decoder-only 模型;自定义一个python文件:from lavis.models import load_model_and_preprocessimport gradio as grimport 最终训练结果权重保存在配置文件的output_dir路径下:加载微调后的权重:from lavis.models import load_model_and_preprocessimport gradio as grimport
import osfrom pathlib import Pathfrom threading import Threadfrom typing import Unionimport gradio as grimport
1.经典案例简单的RGB转灰度保持一贯作风简单展示一下如何使用import gradio as grimport cv2def to_black(image): output = cv2.cvtColor import gradio as grimport cv2def to_black(image): output = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
import gradio as grimport os import openai from langchain.chains import ConversationalRetrievalChain
以下是一个简单的例子:import gradio as grimport tensorflow as tfimport numpy as np# 加载预训练的模型model = tf.keras.applications.InceptionV3
import gradio as grimport numpy as npdef flip(im): return np.flipud(im)demo = gr.Interface( flip import gradio as grimport numpy as npimport time#生成steps张图片,每隔1秒钟返回def fake_diffusion(steps): for
在浏览器中访问 http://localhost:7860 使用应用注意: 使用前需在阿里云DashScope平台申请API密钥"""import gradio as grimport dashscopefrom 代码分解5.1 导入和初始化import gradio as grimport dashscopefrom dashscope import ImageSynthesisimport requestsimport
/run_gradio_stream.pyimport gradio as grimport timeimport osfrom transformers import AutoTokenizer, TextIteratorStreamerfrom
通过qwen-turbo模型生成聊天机器人演示import gradio as grimport dashscopeimport osfrom dashscope import Generationfrom
>"), )output = tokenizer.batch_decode(generate_ids)[0]print(output)模型部署import gradio as grimport
from typing import Listimport argparseimport gradio as grimport torchfrom threading import Threadfrom
import AutoTokenizer, AutoModelForCausalLMfrom modelscope import snapshot_downloadimport gradio as grimport
langgraph.graph import StateGraph, ENDfrom typing import Dict, TypedDict, List, Optionalimport gradio as grimport