Search Results for "git:/git.code.sf.net/p/docfetcher/code" - Page 2
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Showing 57 open source projects for "git:/git.code.sf.net/p/docfetcher/code"
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Outplacement, Executive Coaching and Career Development | CareermindsBy helping to avoid the potential risks of RIFs or layoffs through our global outplacement services, companies can move forward with their goals while preserving their internal culture, employer brand, and bottom lines.
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1
Intelligent Java
Integrate with the latest language models, image generation and speech
...The library provides an intuitive functions for sending input to models like ChatGPT and DALL·E, and receiving generated text, speech or images. With just a few lines of code, you can easily access the power of cutting-edge AI models to enhance your projects. Access ChatGPT, GPT3 to generate text and DALL·E to generate images. OpenAI is preferred for quality results without tuning. Generate text; Cohere allows you to generate a language model to suit your specific needs. Generate audio from text; Access DeepMind’s speech models. ... -
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VALL-E
PyTorch implementation of VALL-E (Zero-Shot Text-To-Speech)
We introduce a language modeling approach for text to speech synthesis (TTS). Specifically, we train a neural codec language model (called VALL-E) using discrete codes derived from an off-the-shelf neural audio codec model, and regard TTS as a conditional language modeling task rather than continuous signal regression as in previous work. During the pre-training stage, we scale up the TTS training data to 60K hours of English speech which is hundreds of times larger than existing systems.... -
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OpenAI Web Application
A web application that allows users to interact with OpenAI's models
...Responses are displayed in a chat-like format. Select Models (Davinci, Codex, DALL·E, Whisper) based on your needs. Create AI Images (DALL·E). Audio-Text Transcribe (Whisper). Highlight code syntax. Type in the input field and press enter or click on the send button to make a request to the OpenAI API. Use control+enter to add line breaks in the input field. Responses are displayed in the chat-like format on top of the page. Generate code, including translating natural language to code. Take advantage of DALL·E models to generate AI images. ... -
4
Yodd's AI Chat
This app uses the OpenAISwift library, ChatGPTSwift library and OpenAI
...Apparenlty you need to have some credits on your OpenAI account, if you don't have them is looks that adding a payment method to your account is enough. If the testflight link is down you can download the source code and build it yourself, or you can install the IPA. With Yodd AI Chat, you can also generate images to accompany your messages, adding a new level of creativity and personalization to your conversations. Plus, you can save, listen to, and delete messages. -
Intelligent predictive dialer for outbound call centerOur autodialer software can massively increase productivity by dropping busy, unanswered and disconnected line, passing calls answered by real people back to your agents, and leaving messages on answering machines.
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DeepMozart
Audio generation using diffusion models
Audio generation using diffusion models in PyTorch. The code is based on the audio-diffusion-pytorch repository. -
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CPT
CPT: A Pre-Trained Unbalanced Transformer
A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation. We replace the old BERT vocabulary with a larger one of size 51271 built from the training data, in which we 1) add missing 6800+ Chinese characters (most of them are traditional Chinese characters); 2) remove redundant tokens (e.g. Chinese character tokens with ## prefix); 3) add some English tokens to reduce OOV. Position Embeddings We extend the max_position_embeddings from 512 to 1024. We... -
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PerlPP
Perl preprocessor - embed Perl source in any file
...The following commands work mostly analogously to their C preprocessor counterparts. but $fn can be determined programmatically. Note that defines set with -D or -s do not take effect until after the script has been generated, which is after the macro code runs. -
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Minimal text diffusion
A minimal implementation of diffusion models for text generation
A minimal implementation of diffusion models of text: learns a diffusion model of a given text corpus, allowing to generate text samples from the learned model. The main idea was to retain just enough code to allow training a simple diffusion model and generating samples, remove image-related terms, and make it easier to use. To train a model, run scripts/train.sh. By default, this will train a model on the simple corpus. However, you can change this to any text file using the --train_data argument. Note that you may have to increase the sequence length (--seq_len) if your corpus is longer than the simple corpus. ... -
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AI Atelier
Based on the Disco Diffusion, version of the AI art creation software
Based on the Disco Diffusion, we have developed a Chinese & English version of the AI art creation software "AI Atelier". We offer both Text-To-Image models (Disco Diffusion and VQGAN+CLIP) and Text-To-Text (GPT-J-6B and GPT-NEOX-20B) as options. Making available complete source code of licensed works and modifications, which include larger works using a licensed work, under the same license. Copyright and license notices must be preserved. When a modified version is used to provide a service over a network, the complete source code of the modified version must be made available. Create 2D and 3D animations and not only still frames (from Disco Diffusion v5 and VQGAN Animations). ... -
Accounting practice management softwareCanopy is a cloud-based practice management software for accounting and tax firms, offering tools for client engagement, document management, workflow automation, and time & billing. Its Client Engagement platform centralizes interactions with a secure portal, customizable branding, and email integration, while the Document Management system enables organized, paperless file storage. The Workflow module enhances visibility into tasks and projects through templates, task assignments, and automation, reducing human error. Additionally, the Time & Billing feature tracks billable hours, generates invoices, and processes payments, ensuring accurate financial management. With its comprehensive features, Canopy streamlines operations, reduces stress, and enhances client experiences.
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RQ-Transformer
Implementation of RQ Transformer, autoregressive image generation
...A short sequence length is important for an AR model to reduce its computational costs to consider long-range interactions of codes. However, we postulate that previous VQ cannot shorten the code sequence and generate high-fidelity images together in terms of the rate-distortion trade-off. -
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bert4keras
Keras implement of transformers for humans
...A cleaner, lighter version of bert for keras. This is the keras version of the transformer model library re-implemented by the author and is committed to combining transformer and keras with as clean code as possible. The original intention of this project is for the convenience of modification and customization, so it may be updated frequently. Load the pre-trained weights of bert/roberta/albert for fine-tune. Implement the attention mask required by the language model and seq2seq. Pre-training code from zero (supports TPU, multi-GPU, please see pertaining). ... -
12
CIPS-3D
3D-aware GANs based on NeRF (arXiv)
3D-aware GANs based on NeRF (arXiv). This repository contains the code of the paper, CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis. The problem of mirror symmetry refers to the sudden change of the direction of the bangs near the yaw angle of pi/2. We propose to use an auxiliary discriminator to solve this problem. Note that in the initial stage of training, the auxiliary discriminator must dominate the generator more than the main discriminator does. ... -
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Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing... -
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GANformer
Generative Adversarial Transformers
This is an implementation of the GANformer model, a novel and efficient type of transformer, explored for the task of image generation. The network employs a bipartite structure that enables long-range interactions across the image, while maintaining computation of linearly efficiency, that can readily scale to high-resolution synthesis. The model iteratively propagates information from a set of latent variables to the evolving visual features and vice versa, to support the refinement of... -
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Accelerated Text
Accelerated Text is a no-code natural language generation platform
...Accelerated Text is a natural language generation tool which allows you to define data descriptions and then generates multiple versions of those descriptions varying in wording and structure. Accelerated Text is a no-code natural language generation platform. It will help you construct document plans which define how your data is converted to textual descriptions. With Accelerated Text you can use such data to generate text for your business reports, your e-commerce platform or your customer support system. Data descriptions require precision. Accelerated Text follows the principle of this strict adherence to data-bound text generation. ... -
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gpt-j-api
API for the GPT-J language mode. Including a FastAPI backend
An API to interact with the GPT-J language model and variants! You can use and test the model in two different ways. These are the endpoints of the public API and require no authentication. Just SSH into a TPU VM. This code was tested on both the v2-8 and v3-8 variants. -
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Old Photo Restoration
Bringing Old Photo Back to Life (CVPR 2020 oral)
We propose to restore old photos that suffer from severe degradation through a deep learning approach. Unlike conventional restoration tasks that can be solved through supervised learning, the degradation in real photos is complex and the domain gap between synthetic images and real old photos makes the network fail to generalize. Therefore, we propose a novel triplet domain translation network by leveraging real photos along with massive synthetic image pairs. Specifically, we train two... -
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Hands-on Unsupervised Learning
Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)
...Author Ankur Patel provides practical knowledge on how to apply unsupervised learning using two simple, production-ready Python frameworks - scikit-learn and TensorFlow. With the hands-on examples and code provided, you will identify difficult-to-find patterns in data. -
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ML for Trading
Code for machine learning for algorithmic trading, 2nd edition
On over 800 pages, this revised and expanded 2nd edition demonstrates how ML can add value to algorithmic trading through a broad range of applications. Organized in four parts and 24 chapters, it covers the end-to-end workflow from data sourcing and model development to strategy backtesting and evaluation. Covers key aspects of data sourcing, financial feature engineering, and portfolio management. The design and evaluation of long-short strategies based on a broad range of ML algorithms,... -
20
Travesty
Parody text generator
...Literary critic Hugh Kenner and computer scientist Joseph O'Rourke introduced their text scrambler "Travesty" in an issue of BYTE magazine 1984. See the Wikipedia page for more information. The code has been mostly preserved, I've just added a GUI to make it easier to play around with the options and included a copy of Alice in Wonderland. A Windows binary is available on the releases page. Parody generators are computer programs which generate text that is syntactically correct, but usually meaningless, often in the style of a technical paper or a particular writer. ... -
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Awesome AI-ML-DL
Awesome Artificial Intelligence, Machine Learning and Deep Learning
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics. This repo is dedicated to engineers, developers, data scientists and all other professions that take interest in AI, ML, DL and related sciences. To make learning interesting and to create a place to easily find all the necessary material. Please contribute, watch, star, fork and share the repo with others in your community. -
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Deep Exemplar-based Video Colorization
The source code of CVPR 2019 paper "Deep Exemplar-based Colorization"
The source code of CVPR 2019 paper "Deep Exemplar-based Video Colorization". End-to-end network for exemplar-based video colorization. The main challenge is to achieve temporal consistency while remaining faithful to the reference style. To address this issue, we introduce a recurrent framework that unifies the semantic correspondence and color propagation steps. -
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commit-autosuggestions
A tool that AI automatically recommends commit messages
...CodeBERT: A Pre-Trained Model for Programming and Natural Languages introduces a pre-trained model in a combination of Program Language and Natural Language(PL-NL). It also introduces the problem of converting code into natural language (Code Documentation Generation). We can use CodeBERT to create a model that generates a commit message when code is added. However, most code changes are not made only by add of the code, and some parts of the code are deleted. We plan to slowly conquer languages that are not currently supported. To run this project, you need a flask-based inference server (GPU) and a client (commit module). ... -
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GIMP ML
AI for GNU Image Manipulation Program
This repository introduces GIMP3-ML, a set of Python plugins for the widely popular GNU Image Manipulation Program (GIMP). It enables the use of recent advances in computer vision to the conventional image editing pipeline. Applications from deep learning such as monocular depth estimation, semantic segmentation, mask generative adversarial networks, image super-resolution, de-noising and coloring have been incorporated with GIMP through Python-based plugins. Additionally, operations on... -
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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...
