Show HN: Scaffolder, CLI tool to generate project structure, taken from YAML https://ift.tt/gK5F3EQ

Show HN: Scaffolder, CLI tool to generate project structure, taken from YAML Scaffolder is a CLI tool written in Golang to instantly generate skeleton project structure with boilerplate code, that's taken from configurable YAML file, to quickly kick-start your project I was tired of manually creating the project structure, with all those folder, files... So I decided to create a CLI tool that allows you to instantly generate skeleton projects, based on a reusable YAML file with boilerplate code if specified. YAML is very easy for both humans and programs to work with and parse, hence why it's the most logical choice in context of Scaffolder. Check out the GitHub page for detailed description and examples :) https://ift.tt/hGjzv3R July 23, 2023 at 01:18PM

Show HN: Write Excel Formulas in Seconds with AI https://ift.tt/Q6ce7EF

Show HN: Write Excel Formulas in Seconds with AI https://ift.tt/XDGSE36 July 23, 2023 at 11:07AM

Show HN: Interesting Maps https://ift.tt/dnoPFjO

Show HN: Interesting Maps https://ift.tt/fCHFviQ July 23, 2023 at 02:40AM

Show HN: Fastest way to convert a PDF table to Excel https://ift.tt/usAB0ha

Show HN: Fastest way to convert a PDF table to Excel We built a Windows app to convert PDF tables to Excel. You just have to take a screenshot of the table. Why try yet another app when there's so many PDF to Excel converters? It's faster, easier to use and more accurate than other converters (including Excel's Power Query). I would be interested in hearing any feedback. https://table2xl.com July 23, 2023 at 01:43AM

Show HN: Chitchat, an easy-to-use, cross-platform, chat-based LLM interface https://ift.tt/lbeuUvh

Show HN: Chitchat, an easy-to-use, cross-platform, chat-based LLM interface Just finished the first draft of my weekend project. Sadly my industry is far away from all the exciting machine learning developments happening right now, so I wrote this project as my first exploration into the world of LLMs. It's not perfect, but I'm excited to see where the project goes from here! https://ift.tt/OaxctPQ My main motivations were: - Easy-of-use: Many models are supported out-of-the-box so users don't have to figure out how to download, where to save, etc. - Intuitive: A clean interface - Cross platform: The project is written in Rust and cross-compiled to other platforms. You don't have to have Python or the C++ toolchain installed to use. - Chat-based experience: Model sessions are persisted so the model is contextually aware of your conversation. https://ift.tt/A24vhun July 22, 2023 at 10:06PM

Show HN: Vanity, Recognition and Fighting Perfectionism – Buildlog for Git Vain https://ift.tt/1N2CpXm

Show HN: Vanity, Recognition and Fighting Perfectionism – Buildlog for Git Vain https://ift.tt/yRInxqX July 22, 2023 at 02:19PM

Show HN: I trained a 65B LLM on my texts to talk to myself (details inside) https://ift.tt/j3Fxlic

Show HN: I trained a 65B LLM on my texts to talk to myself (details inside) I trained the 65b model on my texts so I can talk to myself. It's pretty useless as an assistant, and will only do stuff you convince it to, but I guess it's technically uncensored? I'll leave it up for a bit if you want to chat with it. I posted this to Reddit and had several hundred people talking to it. Salient points from that discussion: LLAMA 1 65b Rank 128 5 epochs Batch size 1, 256 cutoff Trained in the Oobabooga suite using bitsandbytes 4-bit quantization for the lora Loss around 1.5 seems to give the most coherent results Trained on raw text dumps that is then parsed by a crappy Blazor Server app I threw together in a few hours. Text format is just "Sender:The Message\n" Trained on 2x 3090 Training took about 16 hours at a 90% power cap on the 3090's Trained on ~30k texts (I talk a lot, that was just 2 years) There's nothing telling it that it's a robot, though it sometimes seems to know It was largely inspired by the Unreal Engine lora tutorial I generated a list of fake names and addresses, pulled a list of my contacts, and then scripted out swapping the names and addresses for fictitious PII. I don't really send other sensitive data through text and my account is so thoroughly associated with my real name/location that the data leakage risk is manageable for the short period of time I'll have this available. It tends to halucinate fake PII as well which I think is partially a side effect of the data scrubbing. You'll notice it says things like that I live at 420 Ligma. I'll need to mix in some actual assistant tasks to the dataset before it will actually be useful as an assistant. Right now it's largely just for idle conversation. It's pretty ADHD and will randomly go off on its own tangents. I don't think it's the model. I think I just talk like that. Let me know if you have any questions or comments. I built it for myself, but figured I'll let the communities that have taught and entertained me so much play with it a little, too. Note: it says some pretty unhinged stuff. There's absolutely no guardrails. It also tends to talk like you're already friends with history. https://ift.tt/eP7rbO9 July 21, 2023 at 09:31PM