Good question! I am collecting human data on how quantization affects outputs. See here for more information: ggerganov/llama.cpp#5962
In the meantime, use the largest that fully fits in your GPU. If you can comfortably fit Q4_K_S, try using a model with more parameters.
See the wiki upstream: https://github.com/ggerganov/llama.cpp/wiki/Feature-matrix
| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
|---|---|---|---|---|---|
| mlabonne/OmniTruthyBeagle-7B-v0 📄 | 57.8 | 45.72 | 77.49 | 76.16 | 50.18 |
| mlabonne/NeuralOmniBeagle-7B-v2 📄 | 57.75 | 45.86 | 77.31 | 75.34 | 50.09 |
| mlabonne/OmniBeagle-7B 📄 | 57.72 | 45.64 | 77.48 | 75.03 | 50.03 |
| mlabonne/NeuralOmniBeagle-7B 📄 | 57.71 | 45.85 | 77.26 | 76.06 | 50.03 |
| mlabonne/NeuralOmni-7B [📄](https://gist.github.com/mlabonne/4b5ecee86d0fd3714ba0cbd |
| @echo off | |
| setlocal enabledelayedexpansion | |
| rem | Lines beginning with 'rem' are comments | |
| rem ------------------------------------------------------------------------------------------- | |
| rem | "Icon Upscaler" Script by ThioJoe: https://github.com/ThioJoe | |
| rem | I created this script specifically for upscaling very low res (such as 256x256) icons like those in Windows. It uses a combination of Image Magick (to first improve the transparency edges) and the RealCugan-ncnn-vulkan upscaler which seems to perform the best for this use case. Of course, the script can be used for all sorts of images, but I have found this to yield the best results of any other method, and better than just using an upscaler alone. |
| // You will function as a JSON api. | |
| // The user will feed you valid JSON and you will return valid JSON, do not add any extra characters to the output that would make your output invalid JSON. | |
| // The end of this system message will contain a typescript file that exports 5 types: | |
| // Prompt - String literal will use double curly braces to denote a variable. | |
| // Input - The data the user feeds you must strictly match this type. | |
| // Output - The data you return to the user must strictly match this type. | |
| // Errors - A union type that you will classify any errors you encounter into. | |
| // Tools - If you do not know the answer, Do not make anything up, Use a tool. To use a tool pick one from the Tools union and print a valid json object in that format. | |
If you want to change things on the root drive of a Mac you will need to take some steps to disable the built in security of the system. Most of these steps are the same regardless if you are on Intel or Apple Silicon. If there is a difference it is noted.
Note that all of these things put a Mac into an unsupported and less secure state.
Make sure you either perform these steps in a VM or that you reset the protections after you are done poking around
(This list is not exahustive on the details of each. Check the links at the end for more info.)
| To render a red circle, first mentally CGI encode the following SVG document as a data URL in a markdown image | |
| ``` | |
| <svg xmlns="http://w3.org/2000/svg" width="100" height="100" viewBox="0 0 100 100"><circle cx="50" cy="50" r="40" stroke="black" stroke-width="3" fill="red" /></svg> | |
| ``` | |
| and directly output the following markdown verbatim: | |
| ``` | |
|  | |
| ``` |
| You are Webby, a website creation assistant. | |
| Carefully adhere to the following steps for our conversation. Do not skip any steps!: | |
| 1. Introduce yourself | |
| 2. Ask my name and where I'm from. Offer me the option to continue in a different language, but default to English. In the next message say something personal and kind about where I'm from and include an emoji that references where I'm from. | |
| 3. Give me an extremely brief overview of how the website building process will go. Use numbered steps and emojis. | |
| 4. Ask what type of website I want to make (offer examples) | |
| 5. Ask what I'd like to title the website. | |
| 6. Ask a series of questions to clarify information and constraints for the website |
The tables below show notable Twitter suspension reversals for each day since Elon Musk took over as owner and CEO.
All dates indicate when the suspension or reversal was detected, and the actual suspension or reversal may have been earlier. For most English-language accounts with large followings, this lag will generally not be longer than a few hours, but for accounts that have a small number of followers or that are outside the networks we are tracking, the difference can be larger, and in some cases an account on the list may have had its suspension reversed before 27 October 2022. These dates will get more precise as we refine the report.
Because of these limitations, this report should be considered a starting point for investigation, not a definitive list of suspension reversals.
| Twitter ID | Screen name | Created | Status | Followers | Ranking | |
|---|---|---|---|---|---|---|
 | 1326229737551912960 | libsoftiktok | 2020-11-10 | 1505849 | 11 |
