Sebastian Ruder @seb_ruder
Multilingual LLMs @cohere • Prev: @GoogleDeepMind • Newsletter: https://t.co/7JGh2qpG98 ruder.io Berlin, Deutschland Joined September 2014-
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Command R+ The Top Open-Weights LLM + RAG and Multilingual Support My highlights on the release of the latest Cohere models and why I'm excited for LLM research. newsletter.ruder.io/p/command-r
Excited to announce the Compass Beta, a very powerful multi-aspect data search system powered by a new embedding model, Compass. We're looking for help stress-testing the model's capabilities and finding where it breaks. Sign up here: txt.cohere.com/compass-beta/
Introducing Rerank 3! Our latest model focused on powering much more complex and accurate search. It's the fastest, cheapest, and highest performance reranker that exists. We're really excited to see how this model influences RAG applications and search stacks.
我们在增强 Command 处理中文的能力方面进行了大量投资。我很期待看到华语社群将利用它创造什么。请多多提供反馈，以便我们能够改进。
我们在增强 Command 处理中文的能力方面进行了大量投资。我很期待看到华语社群将利用它创造什么。请多多提供反馈，以便我们能够改进。
한국 커뮤니티가 Command R과 R+를 사용하여 어떤 것을 만들어 낼지 매우 기대됩니다! 여러분의 소중한 피드백을 부탁드리며, 개선할 점이 있다면 언제든지 알려주시기 바랍니다.
한국 커뮤니티가 Command R과 R+를 사용하여 어떤 것을 만들어 낼지 매우 기대됩니다! 여러분의 소중한 피드백을 부탁드리며, 개선할 점이 있다면 언제든지 알려주시기 바랍니다.
Command RおよびR+の主要言語として日本語をサポートできることを嬉しく思います。日本語の機能を今後も向上させていくことを最優先事項とします。
Command RおよびR+の主要言語として日本語をサポートできることを嬉しく思います。日本語の機能を今後も向上させていくことを最優先事項とします。
Get ready for Cohere Build Day 🌐 Join our exclusive developer workshop in 4 cities! Dive into our new Command R & R+ models and learn from Cohere experts to develop enterprise-grade AI solutions. Submit your interest to attend now: info.cohere.ai/cohere-build-d…
(((ل()(ل() 'yoav))).. @yoavgo
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🚀 Our latest Adapters library release integrates quantized model training, enabling efficient fine-tuning of LLMs with Q-LoRA, Q-Bottleneck Adapters, or Q-PrefixTuning. 🎉 Check out this notebook to learn how to fine-tune Llama 3 with Q-LoRA 🦙✨: github.com/Adapter-Hub/ad…
Exclusive for @FortuneMagazine: A year ago, I reported on @OpenAI rival @cohere as flying under the radar. Today, it is under pressure to prove its business model-I spoke to CEO @aidangomez about Cohere's latest models, new revenue channels & much more. fortune.com/2024/04/25/coh…
Command R+ is underrated for everyday use 👀. The speed & the balance of good reasoning, concise answers, and nice writing style makes it perhaps the best daily assistant 🔥
@nickfrosst From a French perspective, you have the best LLM on the market. CR+ is the only one that truly understands and speaks French. Bravo and thank you!
we open sourced our chat interface. github.com/cohere-ai/cohe…
CMDR+ is easily becoming my favorite model now that I've had more time to play with it. GG @aidangomez @cohere It's like having GPT4 on my lap, offline. I love the system/style preamble prompt setup.
えらいこっちゃ。Llama3-70BはElyzaTasks100（Command R+による自動評価）においてCommand R+超えてます
We've written up our methods, results, and provided background on the critical underlying research ideas such as DoRA, in a blog post, along with open source code to allow you to replicate and build on our results: answer.ai/posts/2024-04-…
If the rise of LLMs caught you by surprise, here's your chance to get a preview of what's likely to be the next monumental jump in AI capabilities: LLM-backed agents that use software tools In this video, I'll walk you through the concepts and code of building an LLM-backed…
We have just released 🍷 FineWeb: 15 trillion tokens of high quality web data. We filtered and deduplicated all CommonCrawl between 2013 and 2024. Models trained on FineWeb outperform RefinedWeb, C4, DolmaV1.6, The Pile and SlimPajama!
@WolframRvnwlf @ylecun @cohere ‘s secret sauce is that @seb_ruder breathes multilingual
Just updated our benchmark to include the new Cohere Command models and DBRX! See results at vals.ai
Silicon Valley aired 10 years ago this month. Here’s how I would write the 2024 reboot:
Few days ago a plot comparing MMLU scores vs active parameters became quite popular. Active parameters is only relevant if you run the LLM with batch size 1. In production deployment you batch requests, completely changing your conclusions. Below a better graph comparing user…
Training a bilingual model on two identical (cloned) languages with a 90/10 split yields better results *on both languages* than with a 50/50! It also leads to gradients and hidden states which are more aligned across languages. Interested? Check out @antonschafer's new paper!
LLMs can do amazing things these days—not only in their main language (English?), but also in other ones! Our paper identifies a surprising *potential* reason why: language imbalance! (see caveats in 🧵!) arxiv.org/pdf/2404.07982… + @ravfogel T. Hofmann @tpimentelms @ImanolSchlag
LLMs can do amazing things these days—not only in their main language (English?), but also in other ones! Our paper identifies a surprising *potential* reason why: language imbalance! (see caveats in 🧵!) arxiv.org/pdf/2404.07982… + @ravfogel T. Hofmann @tpimentelms @ImanolSchlag
Zuck on: - Llama 3 - open sourcing towards AGI - custom silicon, synthetic data, & energy constraints on scaling - Caeser Augustus, intelligence explosion, bioweapons, $10b models, & much more Enjoy! Links below
It's going to be hard to adapt Llama3 for Indic languages, in my opinion. Here are a few reasons why: 👉🏼 The tokenizer used is TikToken-based, which is not really efficient in tokenizing Indic text despite having a vocabular size of 121k. 👉🏼 unlike sentence-piece based models,…
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