Evaluating Competing LLM Responses with Labelbox in the GCP Ecosystem 🏷️🔍
In this video, we demonstrate how Labelbox seamlessly integrates with the Google Cloud Platform (GCP) ecosystem to support the development and evaluation of large language models (LLMs).
🤖💬 Learn how to explore data assets across various storage repositories, set up annotation projects, and leverage labeled data for fine-tuning and refining LLMs. 📊🎯
Chapters:
- 00:00 Introduction 🎬
- 00:11 Labelbox Integration with GCP Ecosystem 🔗☁️
- 00:45 Purchasing and Data Ingestion 🛒📥
- 01:05 Exploring Data Assets 🔍📂
- 01:20 Rendering Data and Model Comparison 📊🆚
- 01:25 Setting Up an Annotate Project 📝🚀
- 01:30 Attributes of Data Rows 🏷️📋
- 01:37 Customized Attributes and Use Case 🛠️📌
- 01:43 Evaluation Attributes 📈🔍
- 02:05 Labeling Process 🏷️🔄
- 02:27 Ontology Instructions 📚📖
- 02:38 Completion and Submission ✅📤
- 02:51 Moving to Next Data Rows ⏭️📊
- 02:58 Continuation of Labeling 🔁🏷️
- 03:06 Exporting Labeled Data 📤💾
- 03:38 Utilizing Labeled Data in GCP 🔧☁️
👉 Get Access:
[ Ссылка ]
🔗 Labelbox Platform on Google Marketplace:
[ Ссылка ]
🔗 Gemini Pro Information:
[ Ссылка ]
📣 Partnership announcement:
[ Ссылка ]
Don't forget to like 👍, comment 💬, and subscribe 🔔 for more insights into leveraging Labelbox and GCP for your LLM development and evaluation needs! 🚀
#Labelbox #GoogleCloudPlatform #LLM #DataAnnotation #VertexAI #BigQuery #GeminiPro
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