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React
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Based on our record, React seems to be a lot more popular than Unsloth. While we know about 818 links to React, we've tracked only 5 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.
Let's start by preparing a sample application that we want to place in a Docker image. This will be a web application created using the React framework and its create-react-app tool. It will generate a code template and configuration, allowing us to focus on the image creation aspects. - Source: dev.to / about 1 year ago
Python integrates seamlessly with machine learning (TensorFlow, PyTorch) and data analytics stacks (Pandas). Node.js integrates better with frontend JS ecosystems like React, Vue, and Next.js. - Source: dev.to / 9 months ago
Dora AI exemplifies this. Allan Murphy Bruun adds, "What makes it different is its context-aware logic stitching that understands user flows beyond just UI elements." By analyzing Figma designs, it generates React code with state management, saving hours in development. - Source: dev.to / 11 months ago
Import { createFileRoute } from "@tanstack/react-router"; Import logo from "../../logo.svg"; Import "../../App.css"; Export const Route = createFileRoute("/_authenticated/")({ component: AuthenticatedRoute, }); Function AuthenticatedRoute() { return (- Source: dev.to / 12 months ago![]()
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One inspiring example is a developer building a "Todoist Clone" using a combination of React, Node.js, and MongoDB. The developer tapped into open source libraries and community support to create a highly responsive task management application. This project underscores how indie hackers can achieve rapid development and adaptation with minimal budget โ a theme echoed in several indie hacking success stories. - Source: dev.to / about 1 year ago
Unsloth is primarily a fine-tuning tool โ 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 / 3 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 โ quantizing to 4 bits enables fine-tuning 65B+ parameter models on a single consumer GPU with just 3GB VRAM (Unsloth). - Source: dev.to / 3 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 / 11 months 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 / about 1 year ago
Install and configure Unsloth in Colab. - Source: dev.to / about 1 year ago
Vue.js - Reactive Components for Modern Web Interfaces
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!
Next.js - A small framework for server-rendered universal JavaScript apps
Plexe - Build and deploy ML models from natural language
Svelte - Cybernetically enhanced web apps
Minimax Platform - Overview of MiniMax AI models and their capabilities