You're building an app that generates images, transcribes audio, or synthesizes speech. Two API platforms keep showing up in your research: Replicate and deAPI. They run many of the same open-source models and charge per use. - Source: dev.to / 2 months ago

Replicate: Provides APIs for integrating diverse hosted models into shared pipelines. - Source: dev.to / 3 months ago

Running AI models in production typically requires managing complex infrastructure, GPUs, and scaling challenges. Replicate simplifies this by providing a cloud API to run thousands of AI models without managing any infrastructure. - Source: dev.to / 8 months ago

Before diving into how vision prompting works, let’s first look at where we can put it to the test. In this case, we’ll be using several endpoints available on Replicate, which we’ve optimized with Pruna to make them cheaper, faster, and more efficient. All of Pruna’s models are available here. - Source: dev.to / 9 months ago

Take Perplexity they didn’t just call the OpenAI API; they built a full-stack retrieval engine with caching, ranking, and live search inference. Or Replicate, which gives developers an API to run open-source models at scale, no data center required. RunPod makes GPU clusters accessible for indie builders, and Mistral is shipping models that make even GPT-4 blink twice. - Source: dev.to / 9 months 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 / 4 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 / about 1 year ago

Install and configure Unsloth in Colab. - Source: dev.to / over 1 year ago