Hugging Face on Google Cloud
公司规模
Large Corporate
国家
- United States
产品
- Hugging Face Deep Learning Containers (DLCs)
- Google Kubernetes Engine (GKE)
- Vertex AI
- Text Generation Inference (TGI) DLC
- Text Embeddings Inference (TEI) DLC
技术栈
- PyTorch
- Transformers
- TRL
- Sentence Transformers
- Diffusers
实施规模
- Enterprise-wide Deployment
影响指标
- Digital Expertise
- Productivity Improvements
技术
- 平台即服务 (PaaS) - 数据管理平台
- 分析与建模 - 机器学习
- 平台即服务 (PaaS) - 设备管理平台
适用行业
- Software
- Professional Service
适用功能
- 产品研发
- 商业运营
用例
- 边缘计算与边缘智能
- 机器状态监测
- 预测性维护
服务
- 云规划/设计/实施服务
- 软件设计与工程服务
- 系统集成
关于客户
Hugging Face is a leading company in the field of artificial intelligence, known for its open-source models and tools that facilitate machine learning and natural language processing. The company collaborates with Google Cloud to enhance the capabilities of businesses by providing them with the latest AI models and cloud features. Hugging Face's offerings are particularly beneficial for organizations looking to leverage AI for various applications, as they provide a seamless integration with Google Cloud's infrastructure. This collaboration allows businesses to train and deploy models efficiently, utilizing the power of Google Cloud's hardware and services. Hugging Face's Deep Learning Containers (DLCs) are a key component of this offering, providing pre-configured environments for machine learning tasks, thus reducing the complexity and time required for setup and maintenance.
挑战
Hugging Face collaborates with Google to enable companies to build their own AI using the latest open models and cloud features. The challenge is to provide an optimized environment for machine learning workloads without requiring configuration or maintenance from the users. This involves integrating Hugging Face models with Google Cloud services like Google Kubernetes Engine (GKE) and Vertex AI, and ensuring compatibility with various hardware options available on Google Cloud.
解决方案
Hugging Face has developed Deep Learning Containers (DLCs) specifically for Google Cloud customers, allowing them to run machine learning workloads in an optimized environment. These DLCs are Docker images pre-installed with essential deep learning frameworks and libraries, such as Transformers, Datasets, and Tokenizers. They enable users to serve and train models without the need for building and optimizing environments from scratch. The DLCs support training on both GPUs and TPUs, and include libraries like TRL, Sentence Transformers, and Diffusers. For inference, Hugging Face offers a general-purpose PyTorch inference DLC, as well as specialized DLCs for high-performance text generation and embedding models. These containers are hosted in the Google Cloud Artifact Registry and can be utilized across various Google Cloud services, including Google Kubernetes Engine (GKE), Vertex AI, and Cloud Run. Hugging Face also provides no-code integrations for easy deployment and advanced options for direct container usage, ensuring flexibility and ease of use for Google Cloud customers.
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