Search Results for "1000"
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Showing 8 open source projects for "1000"
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MyChatGPT
OSS standalone ChatGPT client
...I also don't want to pay for a service that I use only a few times a month. Even with relatively high usage this client is much cheaper. A ChatGPT conversation can hold 4096 tokens (about 1000 words). The ChatGPT API charges 0.002$ per 1k tokens. Every message needs the entire conversation context. So if you have a long conversation with ChatGPT you pay about 0.008$ per message. ChatGPT needs to send 2500 (messages with full conversation context) a month to pay the same as the ChatGPT subscription. -
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OpenaiBot
Refractoring ChatBot+LLM, Gpt-3.5-turbo, ChatGPT Bot/Voice Assistant
...Designed for full compatibility and strong scalability, adapting to different application scenarios. Features a memory pool that guarantees the storage of context memory for up to 1000 rounds. -
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A Survey of Surveys
A collection of 1000+ survey papers on Natural Language Processing
A Survey of Surveys is a large curated repository that collects and organizes survey papers related to natural language processing, machine learning, and artificial intelligence research. The project aims to provide a centralized index of survey literature that summarizes major developments across different subfields of AI. Rather than focusing on code implementations, the repository functions as an academic resource that helps researchers quickly discover comprehensive survey papers... -
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Corporate Bullshit Generator
A high-performance random text generator focused on corporate bullshit
The Corporate Bullshit Generator is a best-in-class, high-performance random text generator that is focused on corporate bullshit. It is able to produce, per second, 1000 A4 full pages of inspired sentences like "Our turn-key branding strategy drives corporate, scalable, wide-ranging and profit-oriented idiosyncratic incentives." Online app: visit ----> https://tinyurl.com/y3d6wyd6 . Alire crate: https://alire.ada.dev/crates/cbsg Mirror: https://github.com/zertovitch/cbsg -
5
ImageAI
A python library built to empower developers
...You will find features supported, links to official documentation as well as articles on ImageAI. ImageAI is widely used around the world by professionals, students, research groups and businesses. ImageAI provides API to recognize 1000 different objects in a picture using pre-trained models that were trained on the ImageNet-1000 dataset. The model implementations provided are SqueezeNet, ResNet, InceptionV3 and DenseNet. ImageAI provides API to detect, locate and identify 80 most common objects in everyday life in a picture using pre-trained models that were trained on the COCO Dataset. -
6
Mycroft
Mycroft Core, the Mycroft Artificial Intelligence platform
...Our open-source, modular system can be ported to your device or environment, at any price point. Whether you make voice-assistants, televisions, or microwaves. Whether you have a 5-room BnB or a 1000-room hotel. Your customers will get access to all the necessities of a voice assistant. Our software and essential services are free (as in freedom) and also gratis (at no cost to you or them). And especially not at the cost of their (or your) privacy! Your customers will be able to upgrade their experience with premium content and services. ... -
7
CLIP Guided Diffusion
A CLI tool/python module for generating images from text
...Non-square Generations (experimental) Generate portrait or landscape images by specifying a number to offset the width and/or height. Uses fewer timesteps over the same diffusion schedule. Sacrifices accuracy/alignment for quicker runtime. options: - 25, 50, 150, 250, 500, 1000, ddim25,ddim50,ddim150, ddim250,ddim500,ddim1000 (default: 1000) Prepending a number with ddim will use the ddim scheduler. e.g. ddim25 will use the 25 timstep ddim scheduler. This method may be better at shorter timestep_respacing values. Multiple prompts can be specified with the | character. You may optionally specify a weight for each prompt. -
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Reliable Metrics for Generative Models
Code base for the precision, recall, density, and coverage metrics
Reliable Fidelity and Diversity Metrics for Generative Models (ICML 2020). Devising indicative evaluation metrics for the image generation task remains an open problem. The most widely used metric for measuring the similarity between real and generated images has been the Fréchet Inception Distance (FID) score. Because it does not differentiate the fidelity and diversity aspects of the generated images, recent papers have introduced variants of precision and recall metrics to diagnose those...
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