Hugging Face 示例脚本 包括不同的 自监督预训练策略 如 MAE,和 对比图像到文本预训练策略 如 CLIP。这些脚本对于研究社区和愿意在预训练模型上从头训练自定义数据语料的从业者来说是非常宝贵的资源。 Hugging Face 示例脚本:https://github.com/huggingface/transformers/tree/main/examples 自监督预训练策略:https:/...
generator=HuggingFaceLocalGenerator(model="google/flan-t5-large",generation_kwargs={"max_new_tokens":100,"temperature":0.9}) If not set, the Hugging Face default formax_length(= input prompt +max_new_tokens) is 20, which leads almost always to truncated responses. ...
在Hugging Face 上,我们为与社区一起推动人工智能领域的民主化而感到自豪。作为这个使命的一部分,我们从去年开始专注于计算机视觉。开始只是🤗 Transformers 中 Vision Transformers (ViT) 的一个 PR,现在已经发展壮大: 8 个核心视觉任务,超过 3000 个模型,在 Hugging Face Hub 上有超过 1000 个数据集。 自从ViTs...
Hugging Face is most notable for its Transformers library built for natural language processing applications and its platform that allows users to share machine learning models and datasets.This connector is available in the following products and regions:Développer le tableau ServiceClassRegions Logic ...
Hugging Face is looking out for the creatives.Credit: Collage by We Are / Getty Images Hugging Face wants to help users fight back against AI deepfakes. The company that develops machine learning tools and hosts AI projects also offers resources for the ethical development of AI. That now inc...
Hugging Face will offer users, developers, and data scientists the tools needed to get to high-level results and create better models and tools.
A text-to-image generator using stable diffusion API from Hugging Face reactstable-diffusionhugging-face-api UpdatedMar 6, 2023 JavaScript ogios/huggingchat-api-Chinese.ver Star5 登录Huggingchat 与对话,配合有道翻译,可以使用"Search web"。Login to hugging-chat, translate response into chinese. "Sear...
The Hugging Face Diffusers library is a one-stop shop for image generation using Stable Diffusion models for text-to-image, image-to-image, & image inpainting.
The AI Comic Factory is an online AI Comic Book Generator platform that allows you to generate your own comic book with the help of Hugging Face Space.
在Hugging Face 上,我们为与社区一起推动人工智能领域的民主化而感到自豪。作为这个使命的一部分,我们从去年开始专注于计算机视觉。开始只是Transformers 中 Vision Transformers (ViT) 的一个 PR,现在已经发展壮大: 8 个核心视觉任务,超过 3000 个模型,在 Hugging Face Hub 上有超过 1000 个数据集。