meta llama 3 fine tuning, rag, and prompt engineering for drug discovery
Published 3 months ago • 17K plays • Length 1:07:41Download video MP4
Download video MP3
Similar videos
-
8:33
what is prompt tuning?
-
1:03:31
meta llama 3 drug discovery generative ai assistant - developments
-
15:17
llama-3 🦙: easiet way to fine-tune on your data 🙌
-
25:18
llama 3 rag demo with dspy optimization, ollama, and weaviate!
-
33:24
fine-tuning llama 3 on a custom dataset: training llm for a rag q&a use case on a single gpu
-
10:46
llama 3.1 70b to llama 3.1 8b with ollama - prompt engineer
-
14:39
llama3.1 fine tuning complete guide on colab
-
2:52
meta’s new llama 3.1 ai model is free, powerful, and risky
-
24:20
"okay, but i want llama 3 for my specific use case" - here's how
-
11:22
llama 3 released - all you need to know
-
3:00
meta ai llama 3 explained (in 3 minutes!)
-
24:02
"i want llama3 to perform 10x with my private knowledge" - local agentic rag w/ llama3
-
12:23
build anything with llama 3 agents, here’s how
-
17:57
how good is llama-3 for rag, routing, and function calling
-
16:31
extending llama-3 to 1m tokens - does it impact the performance?
-
8:55
how to fine tune llama 3 for better instruction following?
-
36:54
meta's llama 3 with hugging face - hands-on guide | generative ai | llama 3 | llm
-
10:12
groq function calling llama 3: how to integrate custom api in ai app?
-
![day 68/75 meta llama 3 fine tuning [ explained ] orpo fine tuning lora and qlora | python genai](https://i.ytimg.com/vi/URM4JE6MbJY/mqdefault.jpg)
7:45
day 68/75 meta llama 3 fine tuning [ explained ] orpo fine tuning lora and qlora | python genai
-
15:02
llama 3 tested!! yes, it’s really that great