Viewing profile — osanseviero

Hi! What implementation are you using? Right now VLLM is the one recommended. llama.cpp is in an early draft

Hi! The model is 8B if you also load the vision and audio components. We just used the text model in LMArena.

Hi! Omar from the Gemma team here. Last time we only released the quantized GGUFs. Only llama.cpp users could use it (+ Ollama, but without vision). Now, we released the unquantize…

Please make sure to update to the latest llama.cpp version

Nat Friedman leads the project. He was GitHub's CEO, among many other things. He funds many interesting ambitious projects, such as the Vesuvius Challenge ( https://scrollprize.org…

Yes, they are still used - Encoder based models have much faster inference (are auto-regressive) and are smaller. They are great for applications where speed and efficiency are key…

Yes, there are a few dozen full open source models (license, code, data, models)

Hi all! I'm Omar from Hugging Face. Happy to answer any questions you might have about Hugging Face in general, llamas, and open ML!

Zephyr 141B is a Mixtral 8x22B fine-tune. Here are some interesting details - Base model: Mixtral 8x22B, 8 experts, 141B total params, 35B activated params - Fine-tuned with ORPO, …

The model is also at https://huggingface.co/xai-org

The dataset has - 2 million patches - 1068x1068 pixel patches - 2.5 trillion pixels Read more in https://huggingface.co/posts/aliFrancis/293058125194160

Hey @godelski! Author of the blog post here. I really appreciate you taking the time to provide all this feedback. This feedback + additional resources are extremely useful. I agre…

Yes, you're correct. I tried to connect a common training problem (gradient explosion and vanishing gradient) with the issue of softmax being sensitive to large values. I agree it'…

Just math, and not even that fancy. Let's say you want to predict if you'll pass an exam based on how many hours you studied (x1) and how many exercises you did (x2). A neuron will…