GPT4All isAn assistant large-scale language model trained based on LLaMa’s ~800k GPT-3.5-Turbo Generations, this modelTrained on a large amount of clean assistant data, including code, stories, and dialogues,can be used as Substitution of GPT4. Example running on an M1 Mac: from direct link or [Torrent-Magnet] download gpt4all-lora-quantized.bin document. To clone this repository, navigate to chat […]
Convert LabelMe to MsCOCO, PascalVOC, Yolo format. As well as splitting the dataset into training, testing, and validation samples; augmenting the transformed dataset with data augmentation; outputting and recording image statistics; and converting the entire dataset to a single resolution. Installing the necessary packages >> pip install -r requirements.txt The list of classes is written
Cerebras GPT is a pre-trained large model in the field of natural language processing open sourced by Cerebras. Its model parameters range from a minimum of 111 million to a maximum of 13 billion, with a total of 7 models. Compared with the industry’s models, Cerebras-GPT is completely open in almost all aspects without any
Bloom is a large language model for natural language processing, containing 176 billion parameters, supporting 46 natural languages (including Chinese) and 13 programming languages, which can be used to answer questions, translate text, extract information fragments from files, and Can be used to generate code like GitHub Copilot. The biggest advantage of the BLOOM model
Vicuna is an open-source chatbot created by fine-tuning the LLaMA base model with approximately 70K user-shared conversations collected from ShareGPT.com using public APIs. onlinedemo To ensure data quality, the development team converted HTML back to markdown and filtered out some inappropriate or low-quality samples.As well as splitting lengthy dialogues into smaller parts to fit the
The full name of the LLaMA language model is “Large Language Model Meta AI”, which is Meta’s new large-scale language model (LLM). parameters vary). It is worth noting that although LaMA-13B (a model with 13 billion parameters) has more than ten times fewer model parameters than OpenAI’s GPT-3 (175 billion parameters), it can surpass the
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Spry is an HTTP middleware framework for the Dart language that makes writing web applications and API servers more enjoyable. import ‘package:spry/spry.dart’; main() { final Spry spray = Spry(); handler(Context context) { context.response.text(‘Hello Spry!’); } spry. listen(port: 3000, handler);} philosophy Spry is a framework for building web applications and APIs. It is designed to be
Stanford Alpaca (Stanford Alpaca) is an instruction-tuned LLaMA model fine-tuned from Meta’s large language model LLaMA 7B. Stanford Alpaca lets OpenAI’s text-davinci-003 model generate 52K instruction-following samples in a self-instruct manner as Alpaca’s training data. The research team has open sourced the training data, codes for generating training data, and hyperparameters, and will release model
Flecs is a lightweight entity-component system for C and C++ that helps in building simulations such as games. Flecs were designed from the ground up with portability in mind. Not only does it run on all major platforms, projects can also use it with different programming languages. Entity Component System (ECS) is a way
Prisma (for Dart) is for Dart and Flutternext generation ORM. Most Popular Databases: Prisma supports PostgreSQL, MySQL, MariaDB, SQL Server, SQLite, MongoDB, and CockroachDB. type safety: Prisma Client is a query builder tailored to your schema. We’ve designed its API to be intuitive and suitable for SQL veterans as well as developers new
D2 is a modern diagramming scripting language that converts text into diagrams. It stands for declarative diagrams, users just need to use descriptive text and it will automatically generate images. Here’s its Hello World: For example, to download the CLI, create a file called input.d2 file, copy and paste the following content, and run this
Lit-LLaMA is an implementation of the nanoGPT-based LLaMA language model that supports quantization, LoRA fine-tuning, and pre-training. Design Principles Simple: single file implementation, no boilerplate code Correct: Numerically equivalent to the original model Optimized: run on consumer hardware or at scale Open source: no strings attached set up Clone repository
nanoGPT claims to be the easiest and fastest database for training/tuning medium-sized GPT, and is still under active development, but the documentation train.pyGPT-2 was reproduced on OpenWebText (trained for about 4 days on an 8XA100 40GB node). Because the code is so simple, it’s easy to modify it to suit your needs, train a new
OrientDB is a high-performance document and graph database, which has a great speed advantage in relational search and traversal, especially when dealing with join operations in traditional relational databases, graph databases have incomparable advantages. Although OrientDB officially provides a Java SDK, there is still a certain learning cost, and manual operation scripts are required. This
