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CloudStack
OpenStack
Amazon EC2
OpenShift
Google Compute Engine
Hostwinds
Docker Compose
AlwaysData
Unsloth
Fireworks AI
Ollama
Plexe
Minimax Platform
Groq Chat
Mistral Forge
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CloudStack is recommended for enterprises and service providers that need a customizable and scalable cloud solution. It is particularly suitable for those who require support for multiple hypervisors and need to integrate with existing infrastructure components. It is also ideal for organizations preferring open-source solutions with active community support.
Based on our record, Unsloth should be more popular than CloudStack. It has been mentiond 6 times since March 2021. 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.
You could look at the Apache Cloudstack project Https://cloudstack.apache.org/index.html. Source: over 4 years ago
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 / 5 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
OpenStack - OpenStack software controls large pools of compute, storage, and networking resources throughout a datacenter, managed through a dashboard or via the OpenStack API.
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!
Amazon EC2 - Amazon Web Services offers reliable, scalable, and inexpensive cloud computing services. Free to join, pay only for what you use.
Ollama - The easiest way to run large language models locally
OpenShift - OpenShift gives you all the tools you need to develop, host and scale your apps in the public or private cloud. Get started today.
Plexe - Build and deploy ML models from natural language