Видео

Wow, thanks so much for this explanation!

Very useful content thank you Sam for your valuable insights into these topic areas

Very helpful, thank you so much

Is it possible to do tagging and extraction at the same time? In the context of event planning, I want the event details (tagging), as well as a list of vendor services and requirements (extraction). I have difficulty forming the class/schema

when im printing the random speaker, im only getting chinese text as output do you have any idea why?

i love this series of introduction ollama!!! a lot!!!

This is good stuff 🙌♥️

oobabooga?

Am I the only one who misses a memory module from Lagent? I'm gonna test this though ASAP

Hello Sam, Thanks to bring this wonderful model to our attention. There is just a confusion in the video between commercial usage and commercial licence: commercial usage is allowed without submitting any form, but with the Open Source licence you might need to Open Source any derivative work (ie finetuning you make for example). If you want to make non open source stuff with it (why would you😊?) you will need to submit the form to obtain a commercial licence, allowing you to do that. It is a quite classic business model in Open Source software

thats a nice SMALL model for function calling alright... appreciate you bringing it to my attention.

If each model gets a higher rating than its predecessors, when will we reach 100? Also, if I don't watch such videos, will this happen later?

Great work and excellent explanation. Thank you

mannnnnnn no china

Fun fact these Chinese models are banned in the USA and can’t be used for a commercial product

What is the agentic aspect? Maybe I don't understand something or missed something?

Thank you, Sam, for once again highlighting the most interesting new models/techniques in this fascinating field. I note InternLM 2.5 explicitly notes that it "supports gathering information from over 100 websites" with an implementation using Lagent. I'm sure a LangChain implementation could be easily created as well. Actually fine tuning models with Sources for information not in the model (like current weather or news) with function calling and JSON support and using LangChain for finer control would be a great method for using smaller local models. (I feel more comfortable using LangChain than a model specific framework, if possible.) I would love to see other models add this approach. I wonder how much this is done in pretraining vs the base model. (guess I'll have to look at the paper 😉).

Cheers to @samw over @sama. Sama is a charlatan grifter. Please can we move on from him. @samw is a much better representative and explainer of what is going on.

thanks! in spanish is regular but good that all evolution :)

ask him what happen in 1989 LOL

Do we have any idea what non-english languages are supported for llama3?

I couldn’t get InternLM to work well with RAG or any embedding. It gives ok answers to simple prompting.

thanks!!

great job mate! And this is a bit like glm4, not sure about the comparison of benchmark. Both are agentic designed, and could be trained with agentic instructions.

No matter how good chinese models are nobody's gonna believe it because the whole country is a big liar and there is no guarantee of anything and everything they produce is cheap versions of something great.. so I would stay away from anything and everything coming from china but still thanks for the video

Kind of interesting that if one of the stronger points of InternLM 2.5 is being able to support agents, I wonder what part of the training data makes it more capable of supporting agents if function calling data only accounts for 16%. Thanks for the video, I'll have to find a way to make time to try it out.

LMDeploy is a quite interesting framework to deploy and quantize most of the Chinese models. It also works in Kaggle fairly well given it supports also older GPUs.

Thanks

Nice

Thanks a lot for this I wish you could consider the continuing process for identifying authentic and fake certificates 🙏🙏🙏

Brilliantly put together points, Sam. I have been seeing them coming and clearly you’ve articulated all of them up well.

pls pls, do new videos as most of the codes show deprecated. These videos are amazing.

This makes so much sense

Requesting a vid on GraphRAG

Thank you! You chose the right examples to whet my attention. Regards.

it doesn't work very well, but it is informative.

I have a huge problem with with all solutions must be a Framework, at best this is a library or even a function. Not saying you but companies/developers.

Very helpful! Thank you! 😎🤖

Thanks for sharing your experience. I want to run this model on my computer. So I wrote Modelfile like below: ---------------------------------------------------- FROM gemma-2-9b-it-Q6_K_L.gguf TEMPLATE """ <start_of_turn>user: {{prompt}}<end_of_turn> <start_of_turn>model: """ PARAMETER stop <end_of_turn> ---------------------------------------------------- And I create model to ollama, so I ran this command ---------------------------------------------------- ollama create ollama create gemma-2-9b-it-Q6_K_L -f ~/gemma-2-9b-it-Q6_K_L/Modelfile ---------------------------------------------------- And I want to run this model, so I ran this command ---------------------------------------------------- ollama run gemma-2-9b-it-Q6_K_L:latest ---------------------------------------------------- Finally, I got an error message.... Error: llama runner process has terminated: signal: aborted (core dumped) How could you run this model on ollama? Thank you.

I'd like to see more examples of applications of LLMs.

Making a one-line call to a free, open-source Python script to save 30, 50, even 70 percent token use is also an option... github.com/jgravelle/TokenMyzer

Hey Sam ... Awesome Video... Really Helpful. Just want to know is there any mechanism for evaluating it.

Thank you so much!!

Gemini 1.5 Pro is much more expensive than 1.0 Pro at this moment. It costs 7-14 times more per mil. tokens

This is actually ery interesting. Concretely, when you use langchain and has satically linked LLMs on some custom tools, how could we redirect this from langchain directly from langchain so the routing is made afterwards ?

❤❤❤

Now that is OPEN 😮 wow. Great work!

kindly make a simple html file and use it

@matthew_berman

I guess this idea similar to CoE that SambaNova use