Search Results for "llama"
Sort By:
Showing 40 open source projects for "llama"
View related business solutions-
Take away the pain and hassle associated with applicant recruitment, hiring, and onboarding with ApplicantStack. Designed for HR professionals and recruiters, ApplicantStack helps streamline the recruiting and onboarding processes to improve productivity and reduce costs. ApplicantStack provides a complete toolkit that includes tools for posting, launching, and advertising jobs, assessing and managing candidates, collaborating with teams, centralizing information for quick hiring and onboarding, and more.
-
Google Cloud is a cloud-based service that allows you to create anything from simple websites to complex applications for businesses of all sizes.
-
1
llama.cpp
Port of Facebook's LLaMA model in C/C++
Inference of LLaMA model in pure C/C++ -
2
Llama Recipes
Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT method
The 'llama-recipes' repository is a companion to the Meta Llama models. We support the latest version, Llama 3.1, in this repository. The goal is to provide a scalable library for fine-tuning Meta Llama models, along with some example scripts and notebooks to quickly get started with using the models in a variety of use-cases, including fine-tuning for domain adaptation and building LLM-based applications with Llama and other tools in the LLM ecosystem. The examples here showcase how to run... -
3
LLaMA.go
llama.go is like llama.cpp in pure Golang
llama.go is like llama.cpp in pure Golang. The code of the project is based on the legendary ggml.cpp framework of Georgi Gerganov written in C++ with the same attitude to performance and elegance. Both models store FP32 weights, so you'll needs at least 32Gb of RAM (not VRAM or GPU RAM) for LLaMA-7B. Double to 64Gb for LLaMA-13B. -
4
LLaMA Efficient Tuning
Easy-to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon
Easy-to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, ChatGLM2) -
Repfabric is a customer relationship management (CRM) software designed specifically for multi-line sales teams (i.e. reps, distributors, wholesalers, dealers, and manufacturers). It streamlines and simplifies the sales process by providing deep integration with email, contacts, calendars, and deal tracking. The platform enables users to track commissions from CRM to sale, make updates directly from mobile devices, and document sales calls using voice-to-text features.
-
5
Chinese-LLaMA-Alpaca 2
Chinese LLaMA-2 & Alpaca-2 Large Model Phase II Project
This project is developed based on the commercially available large model Llama-2 released by Meta. It is the second phase of the Chinese LLaMA&Alpaca large model project. The Chinese LLaMA-2 base model and the Alpaca-2 instruction fine-tuning large model are open-sourced. These models expand and optimize the Chinese vocabulary on the basis of the original Llama-2, use large-scale Chinese data for incremental pre-training, and further improve the basic semantics and command understanding... -
6
Chinese-LLaMA-Alpaca-2 v2.0
Chinese LLaMA & Alpaca large language model + local CPU/GPU training
This project has open-sourced the Chinese LLaMA model and the Alpaca large model with instruction fine-tuning to further promote the open research of large models in the Chinese NLP community. Based on the original LLaMA , these models expand the Chinese vocabulary and use Chinese data for secondary pre-training, which further improves the basic semantic understanding of Chinese. At the same time, the Chinese Alpaca model further uses Chinese instruction data for fine-tuning, which... -
7
-
8
Ollama
Get up and running with Llama 2 and other large language models
Run, create, and share large language models (LLMs). Get up and running with large language models, locally. Run Llama 2 and other models on macOS. Customize and create your own. -
9
LLamaSharp
C#/.NET binding of llama.cpp, including LLaMa/GPT model inference
The C#/.NET binding of llama.cpp. It provides APIs to infer the LLaMa Models and deploy it on the local environment. It works on both Windows, Linux and MAC without the requirement for compiling llama.cpp yourself. Its performance is close to llama.cpp. Furthermore, it provides integrations with other projects such as BotSharp to provide higher-level applications and UI. -
Evolia is a web and mobile platform that connects enterprises with 1000’s of local shift workers and offers free workforce scheduling and time and attendance solutions. Is your business on Evolia?
-
10
llama2-webui
Run any Llama 2 locally with gradio UI on GPU or CPU from anywhere
Running Llama 2 with gradio web UI on GPU or CPU from anywhere (Linux/Windows/Mac). -
11
Alpaca.cpp
Locally run an Instruction-Tuned Chat-Style LLM
Run a fast ChatGPT-like model locally on your device. This combines the LLaMA foundation model with an open reproduction of Stanford Alpaca a fine-tuning of the base model to obey instructions (akin to the RLHF used to train ChatGPT) and a set of modifications to llama.cpp to add a chat interface. Download the zip file corresponding to your operating system from the latest release. The weights are based on the published fine-tunes from alpaca-lora, converted back into a PyTorch checkpoint... -
12
Text Generation Web UI
A gradio web UI for running Large Language Models like LLaMA
A gradio web UI for running Large Language Models like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and GALACTICA. Dropdown menu for switching between models. Notebook mode that resembles OpenAI's playground. Chat mode for conversation and role playing. Instruct mode compatible with Alpaca and Open Assistant formats. Nice HTML output for GPT-4chan. Markdown output for GALACTICA, including LaTeX rendering. Custom chat characters. Advanced chat features (send images, get audio responses with TTS). Very... -
13
LlamaChat
Chat with your favourite LLaMA models in a native macOS app
Chat with your favourite LLaMA models, right on your Mac. LlamaChat is a macOS app that allows you to chat with LLaMA, Alpaca, and GPT4All models all running locally on your Mac. -
14
pyllama
LLaMA: Open and Efficient Foundation Language Models
📢 pyllama is a hacked version of LLaMA based on original Facebook's implementation but more convenient to run in a Single consumer grade GPU. -
15
LocalAI
Self-hosted, community-driven, local OpenAI compatible API
Self-hosted, community-driven, local OpenAI compatible API. Drop-in replacement for OpenAI running LLMs on consumer-grade hardware. Free Open Source OpenAI alternative. No GPU is required. Runs ggml, GPTQ, onnx, TF compatible models: llama, gpt4all, rwkv, whisper, vicuna, koala, gpt4all-j, cerebras, falcon, dolly, starcoder, and many others. LocalAI is a drop-in replacement REST API that’s compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs (and not only... -
16
llamafile
Distribute and run LLMs with a single file
... for the LLaVA model (license: LLaMA 2, OpenAI). LLaVA is a new LLM that can do more than just chat; you can also upload images and ask it questions about them. With llamafile, this all happens locally; no data ever leaves your computer. -
17
ChatGenTitle
A paper title generation model fine-tuned on the LLaMA model
ChatGenTitle: A paper title generation model fine-tuned on the LLaMA model using information from millions of arXiv papers. -
18
bert4torch
An elegent pytorch implement of transformers
An elegant PyTorch implement of transformers. -
19
Dalai
The simplest way to run LLaMA on your local machine
Run LLaMA and Alpaca on your computer. Dalai runs on all of the following operating systems, Linux, Mac, and Windows. Runs on most modern computers. Unless your computer is very very old, it should work. -
20
LLM Foundry
LLM training code for MosaicML foundation models
Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. Large language models (LLMs) are changing the world, but for those outside well-resourced industry labs, it can be extremely difficult to train and deploy... -
21
tinygrad
Deep learning framework
This may not be the best deep learning framework, but it is a deep learning framework. Due to its extreme simplicity, it aims to be the easiest framework to add new accelerators to, with support for both inference and training. If XLA is CISC, tinygrad is RISC. -
22
OpenFlamingo
An open-source framework for training large multimodal models
.... We also welcome contributions! We provide an initial OpenFlamingo 9B model using a CLIP ViT-Large vision encoder and a LLaMA-7B language model. In general, we support any CLIP vision encoder. For the language model, we support LLaMA, OPT, GPT-Neo, GPT-J, and Pythia models. OpenFlamingo is a multimodal language model that can be used for a variety of tasks. It is trained on a large multimodal dataset. -
23
llm-chain
Rust crate for building chains in large language models
We offer a collection of Rust crates packed with features that make working with Large Language Models easy and seamless. With llm-chain, you can focus on building powerful AI applications. Create reusable and easily customizable prompt templates for consistent and structured interactions with LLMs. Build powerful chains of prompts that allow you to execute more complex tasks, step by step, leveraging the full potential of LLMs. Provides seamless integration with LLaMa models, enabling natural... -
24
kotaemon
An open-source RAG-based tool for chatting with your documents
An open-source clean & customizable RAG UI for chatting with your documents. Built with both end users and developers in mind. This project serves as a functional RAG UI for both end users who want to do QA on their documents and developers who want to build their own RAG pipeline. -
25
Tribe AI
Low code tool to rapidly build and coordinate multi-agent teams
Low code tool to rapidly build and coordinate multi-agent teams. Have you heard the saying, 'Two minds are better than one'? That's true for agents too. Tribe leverages on the langgraph framework to let you customize and coordinate teams of agents easily. By splitting up tough tasks among agents who are good at different things, each one can focus on what it does best. This makes solving problems faster and better.