Search Results for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files"
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Showing 21 open source projects for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files"
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Get full visibility and control over your tasks and projects with Wrike.Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
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Securden Privileged Account ManagerDiscover and manage administrator, service, and web app passwords, keys, and identities. Automate management with approval workflows. Centrally control, audit, monitor, and record all access to critical IT assets.
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Text Generation Web UI
Oobabooga - The definitive Web UI for local AI, with powerful features
...Advanced chat features (send images, get audio responses with TTS). Very efficient text streaming. Parameter presets, 8-bit mode. Layers splitting across GPU(s), CPU, and disk. CPU mode, FlexGen, DeepSpeed ZeRO-3, API with streaming and without streaming. LLaMA model, including 4-bit GPTQ. RWKV model, LoRA (loading and training), Softprompts, and extensions. -
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hfapigo
Unofficial (Golang) Go bindings for the Hugging Face Inference API
(Golang) Go bindings for the Hugging Face Inference API. Directly call any model available in the Model Hub. An API key is required for authorized access. To get one, create a Hugging Face profile. -
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Regex
Generate matching and non matching strings based on regex patterns
...Follow the link to Online IDE with created project: JDoodle. Enter your pattern and see the results. By design a+, a* and a{n,} patterns in regex imply an infinite number of characters should be matched. When generating data, that would mean values of infinite length might be generated. It is highly doubtful anyone would require a string of infinite length, thus I've artificially limited repetitions in such patterns to 100 symbols when generating random values. Use a{n,m} if you require some specific number of repetitions. It is suggested to avoid using such infinite patterns to generate data based on regex. -
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KoboldCpp
Run GGUF models easily with a UI or API. One File. Zero Install.
KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models, inspired by the original KoboldAI. It's a single self-contained distributable that builds off llama.cpp and adds many additional powerful features. -
The AI-powered unified PSA-RMM platform for modern MSPs.SuperOps.ai is the only PSA-RMM platform powered by intelligent automation and thoughtfully crafted for the new-age MSP. The platform also helps MSPs manage their projects, clients, and IT documents from a single place.
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LegacyInsight
Legacy reverse engineering tool
LegacyInsight is an AI-powered reverse engineering platform that transforms legacy software systems into comprehensible business logic. Using cutting-edge GenAI, it analyzes legacy and extracts core operations, business rules, and data transformations—all translated into natural language. LegacyInsight supports enterprise-grade systems built on Java, COBOL, NET and other legacy stacks, helping organizations reclaim understanding of business-critical code. -
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TextGen
textgen, Text Generation models
Implementation of Text Generation models. textgen implements a variety of text generation models, including UDA, GPT2, Seq2Seq, BART, T5, SongNet and other models, out of the box. UDA, non-core word replacement. EDA, simple data augmentation technique: similar words, synonym replacement, random word insertion, deletion, replacement. This project refers to Google's UDA (non-core word replacement) algorithm and EDA algorithm, based on TF-IDF to replace some unimportant words in sentences with synonyms, random word insertion, deletion, replacement, etc. method, generating new text and implementing text augmentation This project realizes the back translation function based on Baidu translation API, first translate Chinese sentences into English, and then translate English into new Chinese. ... -
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ShortGPT Lite
Get short and concise answers from GPT 3/GPT 4
Short GPT Lite is a simple tool for Windows/Linux based on OpenAI's GPT3/GPT4 large language model. The main focus is to get quick and concise answers from GPT. ShortGPT is now available on Android : https://play.google.com/store/apps/details?id=io.github.rupeshs.shortgpt_lite ShortGPT basic web version is now available try it for free: https://nolowiz.com/shortgpt-get-short-and-concise-answers-from-gpt-for-free/ -
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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 initialize the new version of models with the old version of checkpoints with vocabulary alignment. ... -
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TextBox
A text generation library with pre-trained language models github.com
...From a model perspective, we incorporate 47 pre-trained language models/modules covering the categories of general, translation, Chinese, dialogue, controllable, distilled, prompting, and lightweight models (modules). From a training perspective, we support 4 pre-training objectives and 4 efficient and robust training strategies, such as distributed data parallel and efficient generation. Compared with the previous version of TextBox, this extension mainly focuses on building a unified, flexible, and standardized framework for better supporting PLM-based text generation models. -
Deliver and Track Online and Live Training Fast and Easy with Axis LMS!Axis LMS enables you to deliver learning and training everywhere through a flexible and easy-to-use LMS that is designed to enhance your training, automate your workflows, and engage your learners.
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10
AI Chatbots based on GPT Architecture
Training & Implementation of chatbots leveraging GPT-like architecture
...It sure seems like there are a lot of text-generation chatbots out there, but it's hard to find a python package or model that is easy to tune around a simple text file of message data. This repo is a simple attempt to help solve that problem. ai-msgbot covers the practical use case of building a chatbot that sounds like you (or some dataset/persona you choose) by training a text-generation model to generate conversation in a consistent structure. This structure is then leveraged to deploy a chatbot that is a "free-form" model that consistently replies like a human. ... -
11
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... -
12
Texar-PyTorch
Integrating the Best of TF into PyTorch, for Machine Learning
...Texar-PyTorch integrates many of the best features of TensorFlow into PyTorch, delivering highly usable and customizable modules superior to PyTorch native ones. Texar-PyTorch (this repo) and Texar-TF have mostly the same interfaces. Both further combine the best design of TF and PyTorch. Data processing, model architectures, loss functions, training and inference algorithms, evaluation, etc. -
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Insert Text
Extends the media pool with an effect for outputting text in the image
...If a "text area" from the meta data has been selected as the text source, an individual setting for the effect can be applied to each image. -
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Accelerated Text
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. Via its user interface, it provides instruments to define how the data should be translated into a descriptive text. -
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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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Text Gen
Almost state of art text generation library
...Text gen is a python library that allow you build a custom text generation model with ease. Something sweet built with Tensorflow and Pytorch(coming soon). Load your data, your data must be in a text format. Download the example data from the example folder. Tune your model to know the best optimizer, activation method to use. -
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Pipeline for training Language Models
Pipeline for training Language Models using PyTorch.
Pipeline for training Language Models using PyTorch. Inspired by Yandex Data School NLP Course (week 03: Language Modeling) Prepared text file with space-separated words on each line. -
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TFKit
Handling multiple nlp task in one pipeline
...You can use tfkit for model training and evaluation with tfkit-train and tfkit-eval. The key to combine different task together is to make different task with same data format. All data will be in csv format - tfkit will use csv for all task, normally it will have two columns, first columns is the input of models, the second column is the output of models. Plane text with no tokenization - there is no need to tokenize text before training, or do re-calculating for tokenization, tfkit will handle it for you. ... -
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Aida Lib
Aida is a language agnostic library for text generation
Aida is a language-agnostic library for text generation. When using Aida, first you compose a tree of operations on your text that includes conditions via branches and other control flow. Later, you fill the tree with data and render the text. A building block is a variable class: Var. Use it to represent a value that you want to control later. A variable can hold numbers (e.g. float, int) or strings. You can create branches and complex logic with Branch. The context, represented by the class Ctx, is useful to create rules that depends on what has been written before. ... -
20
gpt2-client
Easy-to-use TensorFlow Wrapper for GPT-2 117M, 345M, 774M, etc.
...It features a Transformer model that was brought to light by the Attention Is All You Need paper in 2017. The model has 4 versions - 124M, 345M, 774M, and 1558M - that differ in terms of the amount of training data fed to it and the number of parameters they contain. Finally, gpt2-client is a wrapper around the original gpt-2 repository that features the same functionality but with more accessiblity, comprehensibility, and utilty. You can play around with all four GPT-2 models in less than five lines of code. Install client via pip. The generation options are highly flexible. ... -
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Market Reporter
Automatic Generation of Brief Summaries of Time-Series Data
Market Reporter automatically generates short comments that describe time series data of stock prices, FX rates, etc. This is an implementation of Murakami et al. This tool stores data to Amazon S3. Ask the manager to give you AmazonS3FullAccess and issue a credential file. For details, please read AWS Identity and Access Management. Install Docker and Docker Compose. Edit envs/docker-compose.yaml according to your environment.
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