➡️ JSON Extraction Scripts and/or ADVANCED-inference Repo Access: [ Ссылка ]
➡️ ADVANCED-fine-tuning Repo: [ Ссылка ]
➡️ Trelis Function-calling Models: [ Ссылка ]
➡️ One-click Fine-tuning & Inference Templates: [ Ссылка ]
➡️ Trelis Newsletter: [ Ссылка ]
➡️ Tip Jar and Discord: [ Ссылка ]

Affiliate Links (support the channel):
- Vast AI - [ Ссылка ]
- RunPod - [ Ссылка ]

Resources:
- Slides: [ Ссылка ]
- One-click-llms: [ Ссылка ]
- Chat interfaces: chat.trelis.com or chatbotui.com

Hat tip to Sagar Desai for his insights and help on this vid. Check out his blog on LLMs here: [ Ссылка ]

Chapters
0:00 Introduction to Data Extraction with Language Models
0:28 Overview of the Video
3:26 Challenges in Data Extraction
5:13 JSON Extraction and YAML Extraction
13:27 Practical Demonstration of Data Extraction Using Open Chat
31:44 Comparing GPT 4 and GPT 3.5 for data extraction
34:37 Comparing Performance of Different Models
40:34 Extracting Data from Long Contexts
51:53 Exploring the Cost of Different Data Extraction Approaches
55:43 Conclusion and Final Thoughts

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