Rohan Paul @rohanpaul_ai
ML Engineer (e/acc) 📌 https://t.co/x0IIWfnOt8 🚀 https://t.co/QEO4CKRl1b Fine-Tuned, Cheaper, Open Large Language Models is Happiness 💡 rohanpaul.gumroad.com/l/python-core-… 📌My Python Book 👉🏼 Joined June 2014-
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Comparison of TensorRT-LLM on consumer hardware vs llama .cpp - by @janframework (blog link in 1st comment) --- Findings - "TensorRT-LLM was: - 30-70% faster than llama.cpp on the same hardware - Consumes less memory on consecutive runs and marginally more GPU VRAM…
Really fantastic paper for a new understanding of In-context Learning in Transformers "Transformers learn in-context" In-context learning refers to the ability of Transformers to adapt their predictions based on the context provided in the input sequence, without the need for…
Recently Microsoft announced "ZeroQuant(4+2): Redefining LLMs Quantization with a New FP6-Centric Strategy for Diverse Generative Tasks" 🔥 📌 It investigates the limitations of existing 4-bit quantization methods like GPTQ for large language models (LLMs), which tend to overfit…
Meta is really taking the leadership position for OSS contributions. Beyond Llama-3 - we have all the below from them (and this not an exhaustive list) - React - PyTorch - React Native - GraphQL - Jest - Flow - Yarn - Hermes - FBT - Prophet - Cassandra - Mercurial (which is…
@abacaj For searching a database? of course it does, context kills RAGs 300%. Cache the dataset in the KV cache, it is better in any way shape or form. RAG will only be used for explainability because it is very easy to explain (and "blame"). (rag is also very hard to get to work..)
The Perplexity of Quantized Llama 3 degrades quite a bit vs quantized Llama 2 But looking at the below Perplexity numbers - Llama 3 has a higher initial perplexity when not quantized vs Llama-2. Possible explanation 👇 Degree of specialization of each model on the Wikitext…
The Perplexity of Quantized Llama 3 degrades quite a bit vs quantized Llama 2 But looking at the below Perplexity numbers - Llama 3 has a higher initial perplexity when not quantized vs Llama-2. Possible explanation 👇 Degree of specialization of each model on the Wikitext… https://t.co/sTAW4EzQk3
NEW VIDEO - Rabbit R1: Barely Reviewable youtu.be/ddTV12hErTc This is the pinnacle of a trend that's been annoying for years: Delivering barely finished products to win a "race" and then continuing to build them after charging full price. Games, phones, cars, now AI in a box
When MKBHD proves a point in one scene - Love his style. 💯 LLM Hallucinations ( oops it's LAM)
GGML Flash Attention support merged into llama.cpp github.com/ggerganov/llam…
Improving numerical accuracy is something I've been working to solve on llama.cpp for months now. At first they thought I was trolling, but they've since warmed up to me. I've got other great fixes in the pipeline too. github.com/ggerganov/llam… x.com/rohanpaul_ai/s…
Improving numerical accuracy is something I've been working to solve on llama.cpp for months now. At first they thought I was trolling, but they've since warmed up to me. I've got other great fixes in the pipeline too. github.com/ggerganov/llam… x.com/rohanpaul_ai/s…
Python Coding @clcoding
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neurallambda @neurallambda
207 Followers 152 Following λ/acc. building opensource AGI by jamming turing machines in the latent space
🤨 This fine-tuning is too good to be true? Just tell us what you want your embeddings to excel at, e.g., car insurance claims, financial news, Spanish dialogs. Specify your wish in a prompt; and remember this is your only input to our API. In about 30 mins, we then deliver a…
At Anthropic, we have a company slack channel where we share cool Claude posts and funny memes we’ve seen online. I scrolled back two months to find my 10 favorite things I’ve seen in there since we launched Claude 3🧵
Released dolphin-2.9-llama3-8b-1m with 1 million token context. Thanks to @winglian @Gradient_AI_ @CrusoeCloud Uncensored, be good.
Llama3 as Copilot in VSCode completely private and free! 🤩 In this thread 🧵, I share with you two step-by-step tutorials to use Llama3 running locally on your computer with @ollama and @codegptAI Enjoy VSCode Copilot for free! 👇
Llama3 is really disruptive because it is a much smaller model, so it's much easier to run on all types of different hardware, and much faster. Those two things are like catnip for developers. Within 48 hours it became the most popular model that we run on Groq. The use cases…
Testing InstantSplat with a few frames from Oppenheimer, super fast 3D Gaussian Splatting
Almost $14B raised by AI Startups in 2024 across 600+ rounds Here's my complete database with info on the round, investors, etc Like, comment for free access
@MrCatid @rohanpaul_ai It has wide support for many models, and most importantly CPU + GPU. What do you recommend?
@rohanpaul_ai Flash Attention 2 was release last year.. Not sure why people still use llama.cpp. It lags really far behind all the latest inference tricks
@abacaj 100% this. Anyone claiming otherwise, honestly, has smaller scale use cases.
@abacaj agree even if the long context goes to 10M or 100M how much RAM and extra compute you need feels like a huge waste of energy and time
@abacaj Prolly true, but the paragmatic question is can you make a RAG implementation thats better than what OAI and Anthropic offers
@abacaj For searching a database? of course it does, context kills RAGs 300%. Cache the dataset in the KV cache, it is better in any way shape or form. RAG will only be used for explainability because it is very easy to explain (and "blame"). (rag is also very hard to get to work..)
Delighted to share ✨Med-Gemini✨ - our new family of multimodal models for medicine unlocking new possibilities for health - arxiv.org/pdf/2404.18416 More accurate multimodal conversations about medical images🩻, surgical videos📽️, genomics🧬, ultra-long health records📚, ECGs🫀…
@rohanpaul_ai @janframework Cuda graph is coming, hopefully. But yeah, it's difficult to fill the gap against the vendor itself: github.com/ggerganov/llam…
NEW VIDEO - Rabbit R1: Barely Reviewable youtu.be/ddTV12hErTc This is the pinnacle of a trend that's been annoying for years: Delivering barely finished products to win a "race" and then continuing to build them after charging full price. Games, phones, cars, now AI in a box
Students starting college should consider developing skills like plumbing, electrical, etc. We are going to see some very weird things happen in the near future. Blue-collar skills will be very much in demand and their average total compensation will soon exceed that of the…
Announcing our new dataset: ar5iv 04.2024 🔹2.1 million HTML documents 🔹1 billion formulas in MathML sigmathling.kwarc.info/resources/ar5i…
The Rabbit Hole of Deception: How AI Startups are Exploiting Our Dreams and Delivering Disappointment Marketing products like the Rabbit R1 or Humane AI pin, touting massive potential while delivering a product riddled with usability issues, isn’t just misleading—it’s…
@rohanpaul_ai Feel free to try our LTM Benchmark (long-term memory) It’s focusing on continual learning in context and out of context, and integration of information. github.com/GoodAI/goodai-…
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