4). When to Retrieve? – presents an approach to train LLMs to effectively utilize information retrieval; it first proposes a training approach to teach an LLM to generate a special token, , when it's not confident about the answer to a question.
LLMS
-
Multi-token Prediction Approach Improves LLM Speed
By
–
2). Better and Faster LLMs via Multi-token Prediction – proposes a multi-token prediction approach that performs language modeling by training the predict the following n tokens using n independent output heads…
-
Daily Content on Python, Data Science, Machine Learning, and MLOps
By
–
That's a wrap! If you are interested in any of these below topics: – Python – Data Science – Machine Learning – Data Analysis – LLMs – MLOps Find me → @Sumanth_077 I'm sharing daily content over here.
-
Augment Your LLM Using RAGs NVIDIA Course
By
–
4. Augment your LLM Using RAGs https://
learn.nvidia.com/courses/course
-detail?course_id=course-v1:NVIDIA+S-FX-16+v1
… -
Neural Network Training Scaled 30X Beyond Previous Literature Records
By
–
This system successfully scaled up training of a neural net 30X larger than previously reported in the literature. You're somehow not very knowledgeable & very opinionated about it, referring to it as a "dead end". Even your "Apologies for the confusion" tweet is incorrect.
-
LLMs Tips and Tutorials – Follow for More AI Insights
By
–
If you find this useful, RT to share it with your friends. Don't forget to follow me @Saboo_Shubham_ for more such LLMs tips and tutorials.
-
Explore LLM Apps with RAG in GitHub Repository
By
–
Find all the awesome LLM Apps demo with RAG in the following Github Repo. P.S: Don't forget to star the repo to show your support
-
Full RAG Application Code for GitHub Repository Chat
By
–
Full RAG Application Code to Chat with GitHub Repo
-
Build LLM RAG App Chat GitHub 30 Lines Python
By
–
Build a LLM app with RAG to chat with GitHub in just 30 lines of Python Code (step-by-step instructions):
-
Prompt Engineering with LangChain: Free LinkedIn Learning Course
By
–
Prompt Engineering with LangChain This LinkedIn course by @DataScienceHarp is a great resource for getting started It's over 5 hours long, and Harpreet has been a fantastic member of the community since the early days. Big thanks for all the effort! https://
linkedin.com/learning/promp
t-engineering-with-langchain/create-powerful-llm-driven-applications
…