Hi everyone , I need to embark on large language models using transformer models what do I need to know from RNNs ?
Assuming that you have no previous knowledge i would recommend this roadmap
- Machine Learning Specialization - DeepLearning.AI
- Deep Learning Specialization - DeepLearning.AI
- Generative AI with LLMs - DeepLearning.AI
I hope this help
Best regards
Thank you for your sufficient roadmap
but I have already had some prior knowledge of them, considering that I have covered three first course of whole Deep learning Specialization and currently I am working on final one , RNNs , but due to time constraint I do want to be focused only on transformers so please consider that I do not have to waste my time …
Transformers are in the last week of DLS Course 5.
After that take an LLM course as recommended above.
Yeah … I see … I am engaging with word embedding I will take it up later… Thank u …
So far I have to be able to work with benchmarks , in particular applying some compression methods on them and then try to evaluate them using Hugging face or HELM … Do you know how can I acquire relevant knowledge ?
In addition to what was already recommended:
I believe practicing and putting your recently gained knowledge on GenAI into practice is the essential and decisive step: to get some inspiration: feel free to check out the GPT-powered digital twin of my colleague and fellow mentor @carloshvp, presented in this thread:
https://community.deeplearning.ai/t/say-hello-to-your-peers/440979
Hope that helps, @amirhossein_bozorgkh!
Best regards
Christian
Hi @Christian_Simonis , thanks for the mention! I hope all is good at your side.