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Don't depend on just one AI checker No single checker can guarantee complete confidence. We integrate with leading AI content detectors to give unparalleled confidence that your content appears to be written by a human. One-click, Eight Checks Demo link story.screenspace.io/2161397443/0cb05324
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Content Guardian AI's answer:
Content Guardian is the first multi-AI Content Detector to connect to multiple content checker services simultaneously. 8 checks in 1 click.
Content Guardian AI's answer:
AI is a very fast-paced environment with new advances happening weekly. Not all AI Content Detector models can keep pace. This is where Content Guardian comes in. You can get a much higher level of assurance about the accuracy of the results as we check up to 8 checkers and provide an aggregate score based on our algorithm. We update this regularly so it is reflective of the latest developments in AI LLM.
Content Guardian AI's answer:
We have 3 target audiences. Writers, Media publishers and Education.
Content Guardian AI's answer:
Next.js PHP Javascritp Node.js
Content Guardian AI's answer:
Content Guardian was born out of necessity. We all work with external collaborators and we wanted to have confidence that the content was authentic and original.
We felt having to rely on one AI checker left the business open to a wider margin of risk that it was solely generated by AI, so we started to use multiple AI Content Checkers.
This became very cumbersome for the team, so we decided to create a tool that seamlessly integrates into our workflow whilst connecting to multiple AI Content Checkers. We wanted to build a tool that provides convenience and higher assurance that we can spot unauthentic content.
The tool is ready to be released to the wider world. So here it is!
We will be actively developing the tool with new features and tweaks to make it the best tool it can be.
Based on our record, CUDA seems to be more popular. It has been mentiond 36 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.
For my fellow Windows shills, here's how you actually build it on windows: Before steps: 1. (For Nvidia GPU users) Install cuda toolkit https://developer.nvidia.com/cuda-downloads 2. Download the model somewhere: https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/resolve/main/llama-2-13b-chat.ggmlv3.q4_0.bin In Windows Terminal with Powershell:- Source: Hacker News / 10 months agogit clone https://github.com/ggerganov/llama.cpp.
I use Ubuntu and configuring nvidia drivers is very easy installing from here https://developer.nvidia.com/cuda-downloads. Source: 10 months ago
You have posted almost no information about your Hardware and what exactly you have done. Do you actually have NVIDIA? Have you actually installed CUDA? Also when exactly do you get the error, while installed the python package or later? Source: 10 months ago
EDIT: LINK TO CUDA-toolkit: https://developer.nvidia.com/cuda-downloads. Source: 11 months ago
It's worth noting that you'll need a recent release of llama.cpp to run GGML models with GPU acceleration here is the latest build for CUDA 12.1), and you'll need to install a recent CUDA version if you haven't already (here is the CUDA 12.1 toolkit installer -- mind, it's over 3 GB). Source: 12 months ago
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