ai:faq
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ai:faq [2023/11/25 16:50] – it's about AI, not just LLMs naptastic | ai:faq [2023/12/19 22:10] (current) – [1. WHAT MODEL DO I USE?!] ref controversy about HF leaderboard naptastic | ||
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=====Frequently Asked Questions About Hosting Your Own AI===== | =====Frequently Asked Questions About Hosting Your Own AI===== | ||
- | ====1. | + | ====1. WHAT MODEL DO I USE?!==== |
- | In order to pick the " | + | While this guide will attempt |
- | * your use case, | + | |
- | * what resources you have available, | + | |
- | * what formats you can use, | + | |
- | * what tradeoffs you're willing | + | |
- | We can try to put together a simple guide for " | + | In order to pick a model one must consider: |
+ | - **Compatibility**: | ||
+ | - **Resources**: depending on your situation, you might become limited by GPU speed, VRAM, CPU speed, DRAM, hard disk space, or (less likely) bandwidth. | ||
+ | - **Tradeoffs**: | ||
+ | - **Surprises**: | ||
+ | - **your use case**. | ||
- | ===Aren't there at least comparisons? | + | This grumpy pile of text is gradually turning into a guide--hopefully not too misguided--for selecting models. |
+ | |||
+ | ===How do I know if my model is compatible with my system? | ||
+ | Probably not 100% guarantee, but... we can reduce the chances of a wasted download. | ||
+ | |||
+ | The situation is really complicated but this is a FAQ so I'll keep it simple: | ||
+ | - **Read the model card.** If it doesn' | ||
+ | - If you know the model will fit completely in VRAM, the best performance comes from GPTQ models. (2023-12; I haven' | ||
+ | - If the model will not fit **completely** in VRAM, you **cannot** use GPTQ; use GGUF instead. | ||
+ | * GGUF comes in multiple quantization formats. You only need to download one. Use Q5_K_M if you're not sure. | ||
+ | |||
+ | More details on the formats can be found [[ai: | ||
+ | |||
+ | ===Are | ||
Sure. If you find a good one, send it to me and I'll add a link here. | Sure. If you find a good one, send it to me and I'll add a link here. | ||
- | * [[https:// | + | |
- | * [[https:// | + | * **NOTE**: There is currently (2023-12) controversy about how useful the leaderboard is. This has to do with model contamination. (TODO: add " |
+ | | ||
+ | * [[https:// | ||
- | ===Can' | + | ===Can I at try one before I download it?=== |
Yes. Nap does not know how. Please ask for edit permission and fill this section in. <3 | Yes. Nap does not know how. Please ask for edit permission and fill this section in. <3 | ||
+ | |||
+ | ===Are there any other shortcuts worth taking?=== | ||
+ | I only know of one more: Use a model that someone else in your situation is already using, and they already know it works well. **I'd like to collect a few //(dozen)// such reports here**, if possible. Also what hardware, software, and speed you get, if possible. | ||
+ | |||
+ | * brain: Passes almost every AGI test given over a 40-year period. 90b tensors, 100t weights, runs on a completely proprietary stack. When it's thinking hard, it generates about 14-16 tokens/ | ||
+ | |||
=====Please read these few short paragraphs before diving into The Answers.====== | =====Please read these few short paragraphs before diving into The Answers.====== | ||
===Philosophy=== | ===Philosophy=== | ||
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**Know your goals.** It is **critical** that you know what you want your AI to do for you. Even better if you have it written down. | **Know your goals.** It is **critical** that you know what you want your AI to do for you. Even better if you have it written down. | ||
- | ==What | + | ===What |
- | (At least not yet, or not well) | + | * LLMs generate text and code |
- | * Arithmetic, including counting | + | * They can integrate with... |
+ | * Diffusers generate images | ||
+ | * Upscaling | ||
+ | * Fill-in and fill-out | ||
+ | * Video | ||
+ | * (anything else?) | ||
+ | * Data format conversions | ||
+ | * OCR (" | ||
+ | * Speech-to-text (partially a classification problem; might be better served with other tools.) | ||
+ | * text-to-speech (though this might be better served by other tools) | ||
+ | * **lots of other stuff.** | ||
+ | |||
+ | ===What CAN'T AI do right now?=== | ||
+ | * LLMs are still pretty bad with math. | ||
+ | * Music generation is in its infancy. | ||
+ | * OCR for music transcription is still a hilariously impractical idea. | ||
+ | * **lots of other stuff.** | ||
- | ==What's the best ____?== | + | ===What |
- | This is really not an answerable question. TODO this needs a fuller/ | + | It depends. (I know, I know... I hate that answer too but it's the truth.) |
- | ==What kind of hardware do I need?== | + | Buying a CPU for inference is folly. The only advantage a CPU has is that it usually has more DRAM than the GPU has VRAM, so it can load larger models. The difference in inference speed is at least an order of magnitude. Choosing a GPU, the most important factor is how much VRAM it has. |
- | * see [[formats-faq]] | + | |
- | ==What software do I need?== | + | * For maximum ease and speed, buy Nvidia GPUs. They are really expensive, though. |
- | * Different software is useful for different goals. See the Applications section below for more detailed information about each application. | + | * For a reduced cost, more headaches, and fewer applications that currently support it, buy AMD. They' |
+ | * Intel GPUs have the best price/VRAM ratio of the bunch, but there is almost no support. Getting them to work is (mostly) almost impossible even for experienced system administrators. | ||
- | ==What do all these terms mean?== | + | ===What do all these terms mean?=== |
(nap definitely needs help with this) | (nap definitely needs help with this) | ||
* need a glossary | * need a glossary | ||
- | ==How do I do the thing?== | + | ===How do I do the thing?=== |
* Start with < | * Start with < | ||
* Links to how-to' | * Links to how-to' | ||
- | ==How do I get help with the thing?== | + | ===How do I get help with the thing?=== |
* Read < | * Read < | ||
* Discord servers | * Discord servers |
ai/faq.1700931037.txt.gz · Last modified: 2023/11/25 16:50 by naptastic