Improving AI Shop Integrate Argilla Feedback Dataset & Add Live Records Using Python & Django Views
Large Language models have their weaknesses, and when it comes to live production environments these weaknesses can be amplified. So the solution is to improve the LLM, and to do that, one of the ways is using Fine Tuning.
For Finetuning the LLMs, one requires datasets. These datasets have to be high quality and properly annotated. Argilla helps in getting such well curated Datasets using the inputs the user provides when interacting with LLMs.
Chapter Navigation:
0:00 Intro of Theme
0:45 How to Improve the AI Shop
1:50 Introducing Argilla & Playlist
2:45 Demo of AI Shop
5:10 Reviewing Data Pushed to Argilla
9:25 Walkthrough of Logic
10:35 Code walkthrough of Connect Argilla
15:15 Use of Arg Connect Global Variable
17:00 Disconnect Argilla View
17:35 Code Walkthrough of Argilla Record Creation
20:00 Supporting Function for FB Records
21:45 Reviewing server records
23:00 Using ARG_Connect For Disconnect
23:45 Recap
24:30 Outro
The data and the code is located at
https://github.com/insightbuilder/dja...
https://github.com/insightbuilder/dja...
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The supporting playlists are
The bard Project
• Google Bard LLM : New AI Model in the...
Practical Projects Playlist
• The Future is Here: Large Language Mo...
Huggingface Playlist
• Mastering NLP with Hugging Face: A Co...
Python Data Engineering Playlist
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Python Ecosystem of Libraries
• Mastering the Python Ecosystem: Must-...
ChatGPT and AI Playlist
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AWS and Python AWS Wrangler
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Exploring the Realm of Generative AI: Hardware and Software Discussions
• Exploring the Realm of Generative AI:...
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