kashifr

You can try out TinyLoRA in PEFT main now: https://huggingface.co/docs/peft/main/en/package_reference/t...

Have you tried https://geobase.app/ they recently also had a post about duckdb integration: https://geobase.app/blog/duckdb-1-1-3

A novel and memory-friendly preference alignment method for diffusion models that does not depend on any reference model.

The dataset can be used for training preference models or aligning language models through techniques like Direct Preference Optimization (DPO).

An efficient finetuning approach that reduces memory usage enough to finetune a 65B parameter model on a single 48GB GPU while preserving full 16-bit finetuning task performance!

The title is confusing but refers to the Huggingface Diffusers v0.15 release which brings new pipelines for video and audio to diffusers, showing that diffusion is a great choice for all sorts of generative tasks.

All the steps involved in training a LlaMa model to answer questions on Stack Exchange data with RLHF.

Diffusers now supports CompVis, Stability AI and LAION's Stable Diffusion model weights.

A library of pretrained diffusion models across multiple modalities, such as vision and audio.

With all the terminal recordings I have seen, the content eventually ends up at the bottom. It would be awesome to have the cursor always stay in the middle... any idea if thats possible with Asciinema?

Form my own journey I would say that a good place to start for graphical models might be "Bayesian Reasoning and Machine Learning" by Barber. It's free (http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=...). I haven't read through it, but I've heard good things. However, it doesn't cover some basic things like SVM, RVM, Neural Networks...

For those I'd suggest "Pattern Recognition and Machine Learning" by Bishop. I've read throughout this and it's really well organized and thought out. For more mathematically advanced ML stuff I'd suggest "Foundations of Machine Learning" by Mohri. For a good reference for anything else I'd suggest "Machine Learning: A Probabilistic Perspective" by Murphy. For more depth on graphical models look at "Probabilistic Graphical Models: Principles and Techniques" by Koller.

On the NLP front there's the standard texts "Speech and Language Processing" by Jurafsky and "Foundations of Statistical Natural Language Processing" by Manning.

I also like "An Introduction to Statistical Learning" by James, Witten, Hastie and Tibshirani.

According to the Sandia's Cooler whiter-paper pdf: http://prod.sandia.gov/techlib/access-control.cgi/2010/10025... the limit is due to a "Thermal Brick Wall". Basically due to a lack of progress in heat exchanger technology.

I have visualized this "Brick-Wall" as a graph with data from Wikipedia pdf: http://dl.dropbox.com/u/3215373/Thermal-Brick-Wall.pdf

Hi co-founder of SpacialDB here. Cloud hosted PostGIS is already available as a Heroku plugin, stand-alone and an easy to use API. Check out http://devcenter.spacialdb.com/ for documentation and you can sign up via the Heroku addons page or http://beta.spacialdb.com/

Nokia also has a version of webcl here:

http://projects.developer.nokia.com/webcl