yding

7 ms·

1.
by yding 5mo ago
When you evaluated the tools, what stood out between which ones were better or worse?
2.
Show HN: Lines of Bash to automate LLM code review and fixes(github.com)
2 points by yding 5mo ago|1 comments
3.
Show HN: Blackjack Basic Strategy Practice with DP Edges(twentone.vercel.app)
1 points by yding 7mo ago|0 comments
4.
by yding 2y ago
Makes sense. I wonder if it affects the model output performance (sans quotes), as I could imagine that splitting up the model output to add the quotes could cause it to lose attention on what it was saying.
5.
by yding 2y ago
Thanks Simon. I think this might solve one of the most common questions people ask me: how do I get Perplexity-like inline citations on my LLM output? This looks like model fine tuning rather than after the fact pseudo justification. Do you
6.
by yding 2y ago
As someone who interned at Palm, love this so much!
7.
by yding 2y ago
Depends on the language/standard library. For example in C if your library includes its own HTTP library that's probably not a plus.
8.
by yding 2y ago
Congrats Taranjeet and Deshraj! So after using Mem0 a bit for a hackathon project, I have sort of two thoughts: 1. Memory is extremely useful and almost a requirement when it comes to building next level agents and Mem0 is probably the best
9.
by yding 2y ago
The short answer is he works at Cohere. But longer answer is that the model probably doesn’t matter that much.
10.
by yding 2y ago
Looks great! thanks for sharing your architecture choices here.
11.
by yding 2y ago
Congrats on the launch!
12.
by yding 2y ago
Very cool!
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Libchatty: A faster ChatGPT wrapper in pure C(github.com)
3 points by yding 2y ago|0 comments
14.
by yding 2y ago
Absolutely makes sense!
15.
by yding 2y ago
Congrats! Well deserved achievement by one of the best executing teams.
16.
by yding 2y ago
Training a model with multiple billion floating point parameters on only 100 billion data points feels like a bad idea.
17.
by yding 2y ago
This is really cool! Starred and look forward to seeing how this develops further!
18.
by yding 3y ago
Congrats! Amazing milestone.
19.
by yding 3y ago
Great to see. Not only a wonderful mathematician but also a wonderful human being.
20.
by yding 3y ago
Very cool! Will check it out!
21.
by yding 3y ago
What were the issues you ran into with running LlamaIndex?
22.
by yding 3y ago
Congrats on the launch!
23.
by yding 3y ago
Great explanation!
24.
by yding 3y ago
I’m going to be a contrarian and say that I really appreciate that they went for a high performing/more expensive SoC this time. When I had to buy a SBC last time I couldn’t bring myself to get the Pi 4 because it was missing core feat
25.
ChatGPT's knowledge cutoff was 2 years ago(community.openai.com)
5 points by yding 3y ago|0 comments
26.
by yding 3y ago
Should go without saying to run these only in the most secure sandbox you can find?
27.
by yding 3y ago
The data questions are exactly the things we are working through right now! I think Streamlit is a great way to get started quickly. Would love to talk more about your thoughts around data ingest for prod use cases. yiding@runllama.ai
28.
Show HN: LitLLM the Spiciest LLM Wrapper(github.com)
1 points by yding 3y ago|0 comments
29.
by yding 3y ago
Congrats on the launch!
30.
by yding 3y ago
Currently all of LlamaIndex's text splitters were/are Langchain compatible.

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