Hugging Face 专门开发用于构建机器学习应用的工具。该公司的代表产品是其为自然语言处理应用构建的 transformers 库,以及允许用户共享机器学习模型和数据集的平台 大模型平台 hugging face 国内对标 – 百度千帆 百度智能云千帆大模型平台(以下简称千帆或千帆大模型平台)是面向企业开发者的一站式大模型开发及服务运行平台...
The image captioning model is implemented using the PyTorch framework and leverages the Hugging Face Transformers library for efficient natural language processing. Used streamlit python library for creating interactive web applications. Demo Caption can be generate for any image at link Example Images wit...
其中影响力最大的,也被很多人称为初代 GPT 的 Transformers,截至今天,GitHub Star累积将近 10 万。 这几年,在 Hugging Face 平台上面诞生了无数实用的 AI 预训练模型、数据集。数量之多,品质之高,将其说是 AI 界的 GitHub 也不为过。 今天凌晨,Hugging Face 重磅推出Transformers Agents,在 AI 技术圈再次掀...
Image captions It uses the Hugging Face models to generate image captions. We need to install several python packages. pip install transformers pillow See ausage example. fromlangchain_community.document_loadersimportImageCaptionLoader API Reference:ImageCaptionLoader ...
Hugging Face 专门开发用于构建机器学习应用的工具。该公司的代表产品是其为自然语言处理应用构建的 transformers 库,以及允许用户共享机器学习模型和数据集的平台 大模型平台 hugging face 国内对标 -- 百度千帆 百度智能云千帆大模型平台(以下简称千帆或千帆大模型平台)是面向企业开发者的一站式大模型开发及服务运行平台...
准备ground truth 图片 (image): 这里指的就是真实人脸图片 准备 条件图片 (conditioning_image): 这里指的就是画出来的特征点 准备 说明文字 (caption): 描述图片的文字 针对这个项目,我们使用微软的FaceSynthetics数据集: 这是一个包含了 10 万合成人脸的数据集。你可能会想到其它一些人脸数据集,比如Celeb-A HQ...
Image Caption Hugging Face is an open-source community and data science platform that allows users to share, build, train, and deploy machine learning models. After exploring models available in the Hugging Face model hub, we chose to use theOFA modelbecause as...
Hugging Face gives you a great fast, free way to try multiple versions of the most-buzzed about new AI image-generation engine:Flux. This AI model renders remarkably vivid images. It has several distinctions over earlier AI image generation tools, including: ...
3. [Using BLIP-2 with Hugging Face Transformers](#using-blip-2-with-hugging-face-transformers) 1. [Image Captioning](#image-captioning) 2. [Prompted image captioning](#prompted-image-captioning) 3. [Visual question answering](#visual-question-answering) 4. [Chat-based prompting](#chat-based...
a fine-tuning example before exploring the concept of embeddings in machine learning, understanding how they capture semantic information. By the end of the course, you'll be equipped with the knowledge and skills to tackle a wide range of ML and AI tasks effectively using the Hugging Face ...