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Based on our record, GitHub Codespaces seems to be a lot more popular than Unsloth. While we know about 152 links to GitHub Codespaces, we've tracked only 6 mentions of Unsloth. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Unsloth Desktop is what people have been waiting for. It's just been released as a beta. It's pretty much a single-click install. You download the installer and run it, and from there Unsloth Desktop handles everything else for you. Behind the scenes it scans your machine and determines what needs to be installed. It puts a wrapper around llama.cpp and MLX, which gives you all the power of the top open source... - Source: dev.to / 3 days ago
Unsloth is primarily a fine-tuning tool — it makes QLoRA training 2-5x faster with 50-70% less VRAM. It does NOT run inference. For inference, use Ollama/llama.cpp/MLX. - Source: dev.to / 5 months ago
LoRA is the breakthrough that democratized fine-tuning: by training only 1% of model weights, it reduces GPU/VRAM needs by 10-100x. QLoRA takes it further — quantizing to 4 bits enables fine-tuning 65B+ parameter models on a single consumer GPU with just 3GB VRAM (Unsloth). - Source: dev.to / 6 months ago
Unsloth AI is designed to optimize large language model fine-tuning on modest hardware. It leverages efficient training algorithms to allow even GPUs with 24GB VRAM, like consumer-grade cards, to fine-tune models such as Llama 3 without massive resource demands or overheating risks. - Source: dev.to / about 1 year ago
Lot's of tools for each of those separately (RAG and fine-tuning). We're working on combining them but it's not ready yet. You don't need a big GPU cluster. Fine-tuning is quite accessible via both APIs and local tools. Some suggestions: - getkiln.ai (biased, my tool): let's you try all of the below, and compare/eval the resulting models - API based tuning for closed models: OpenAI, Google Gemini - API based... - Source: Hacker News / over 1 year ago
First, remote dev environments became table stakes. GitHub Codespaces, Gitpod, and self-hosted dev containers became how serious teams worked. Every engineer I know who ships to production now SSHs into a box they didn't provision, edits files with whatever editor is installed, and commits from a terminal. An IDE-bound agent requires you to also forward your IDE to the remote box, which most people don't bother... - Source: dev.to / 5 months ago
This package provides support for managing GitHub Codespaces in Emacs and connecting to them via TRAMP. It provides a handy completing-read UI that lets you choose from all your created codespaces. - Source: dev.to / 6 months ago
GitHub Codespaces provides 60 hours of free compute time every month, which is more than enough for scoped home assignments or interviews. It’s a full VSCode in the browser at github.dev or vscode.dev. - Source: dev.to / 10 months ago
GitHub Codespaces - Cloud development. - Source: dev.to / about 1 year ago
https://github.com/features/codespaces All you need is a well-defined .devcontainer file. Debugging, extensions, collaborative coding, dependant services, OS libraries, as much RAM as you need (as opposed to what you have), specific NodeJS Versions — all with a single click. - Source: Hacker News / over 1 year ago
Fireworks AI - Use state-of-the-art, open-source LLMs and image models at blazing fast speed, or fine-tune and deploy your own at no additional cost with Fireworks AI!
replit - Code, create, andlearn together. Use our free, collaborative, in-browser IDE to code in 50+ languages — without spending a second on setup.
Ollama - The easiest way to run large language models locally
StackBlitz - Online VS Code Editor for Angular and React
Plexe - Build and deploy ML models from natural language
CloudShell - Cloud Shell is a free admin machine with browser-based command-line access for managing your infrastructure and applications on Google Cloud Platform.