Probably the craziest week in Open Source AI (yet):

1. Mistral (in collaboration with Nvidia) dropped Apache 2.0 licensed NeMo 12B LLM, better than L3 8B and Gemma 2 9B. Models are multilingual with 128K context and a highly efficient tokenizer - tekken.

2. Apple released DCLM 7B - truly open source LLM, based on OpenELM, trained on 2.5T tokens with 63.72 MMLU (better than Mistral 7B)

3. HF shared SmolLM - 135M, 360M, & 1.7B Smol LMs capable of running directly in the browser; they beat Qwen 1.5B, Phi 1.5B and more. Trained on just 650B tokens.

4. Groq put out Llama 3 8B & 70B tool use & function calling model checkpoints - achieves 90.76% accuracy on Berkely Function Calling Leaderboard (BFCL).  Excels at API usage & structured data manipulation!

5.  Salesforce released xLAM 1.35B & 7B Large Action Models along with 60K instruction fine-tuning dataset. The 7B model scores 88.24% on BFCL & 2B 78.94%

6. Deepseek changed the game with  v2 chat 0628 - The best open LLM on LYMSYS arena right now - 236B parameter model with 21B active parameters. It also excels at coding (rank #3) and arena hard problems (rank #3)

There's a lot more; Arcee (mergekit) released a series of LLMs, each better than the other, and Numina and HF Numina 72B (based on Qwen 2) and Math datasets, Mixbread with embedding models (english + german) and a lot more!

It's fun to see so many releases next week with L3 405B


I need context, lookup charts, everything seems to be named to be confusing, but how do they each compare to popular closed source models and what are they each better at?


👀
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Have you used Venice Ai? Any thoughts on this? Is it open sourced and privacy focused?


From quick testing, NeMo's logical reasoning performance is very poor compared to even something like phi-3-mini.


Venice uses different Llama3 versions on their servers so privacy has trust involved. If you want sure more privacy you must run the models local.


Wout is correct but it is heads and shoulders above alternatives


Onward 🫡


Checkout unleashed.chat if you interested in privacy


Thanks. What about FreeGPT-2 on nostr:npub126ntw5mnermmj0znhjhgdk8lh2af72sm8qfzq48umdlnhaj9kuns3le9ll


Good and private.


Let's go 🚀


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