PyTorch Reviews

Sabaki Reviews

PyTorch mentions (109)

• Understanding GPT: How To Implement a Simple GPT Model with PyTorch

  In this guide, we provided a comprehensive, step-by-step explanation of how to implement a simple GPT (Generative Pre-trained Transformer) model using PyTorch. We walked through the process of creating a custom dataset, building the GPT model, training it, and generating text. This hands-on implementation demonstrates the fundamental concepts behind the GPT architecture and serves as a foundation for more complex... - Source: dev.to / 3 days ago

• Building a Simple Chatbot using GPT model - part 2

  PyTorch is a powerful and flexible deep learning framework that offers a rich set of features for building and training neural networks. - Source: dev.to / 11 days ago

• Clusters Are Cattle Until You Deploy Ingress

  Oddly enough, sometimes, the best way to learn is by putting forth incorrect opinions or questions. Recently, while wrestling with AI project complexities, I pondered aloud whether all Docker images with AI models would inevitably be bulky due to PyTorch dependencies. To my surprise, this sparked many helpful responses, offering insights into optimizing image sizes. Being willing to be wrong opens up avenues for... - Source: dev.to / 4 days ago

• My Favorite DevTools to Build AI/ML Applications!

  TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more... - Source: dev.to / about 1 month ago

• Functions and operators for Dot and Matrix multiplication and Element-wise calculation in PyTorch

  *My post explains Dot, Matrix and Element-wise multiplication in PyTorch. - Source: dev.to / 2 months ago

Sabaki mentions (8)

• I wonder if these ChatGPT answers will every get nuked

  I've been using ChatGPT since launch and constantly seeking out examples of how others have been using it. A few years ago I started using KataGo with Sabaki to improve my go-playing abilities. I've known about token embeddings in neural networks before ChatGPT was a twinkle in OpenAI's eye. I was there, but I haven't seen everything you've seen, so please show me. If the truth is that ChatGPT has canned responses... Source: about 1 year ago

• Tough semeai during one of my recent tournament games. Black to play and kill the triangled group.

  It's a feature with sabaki, to make it look resemble a real board more. Source: over 1 year ago

• Learning to score a game.

  That said, if you can download some sgfs and view them in a tool like [sabaki]((https://sabaki.yichuanshen.de/), you can try and match the score that the computer reports. You can get SGFs from here - other sources are available. Be sure to find games which were won on points. You can't count a game won by resignation. Source: over 1 year ago

• Contributing to open-source go projects?

  It's a shame because KGS would benefit greatly from a modern client. I think at this point writing a new client from scratch would be preferable, or maybe taking something like [Sabaki](https://sabaki.yichuanshen.de/) and turning it into a KGS client might be viable. Speaking of which, Sabaki is a good option for those looking to contribute to an open source project. Source: over 1 year ago

• DeepMind's Player of Games, a general-purpose game algorithm

  You can also just download pre-trained models. Get those set up and then install Sabaki (https://sabaki.yichuanshen.de/) and connect it to your KataGo... Instant (ok, a few hours probably if it's your first time setting it up) superhuman Go AI. There's even an npm package you can use to process SGF files and automatically score moves as good/questionable/bad + generate variations that were better choices:... - Source: Hacker News / over 2 years ago