Web LLM is aA project to bring large-scale language models and LLM-based chatbots to web browsers.Everything runs in the browser, requires no server support, and is accelerated using WebGPU. This opens up many interesting opportunities to build AI assistants for everyone and achieve privacy while enjoying GPU acceleration. Check out the demo page to try […]
Freedom GPT is a desktop application that allows users to run Alpaca models on their local machines, built with Electron and React. need Run the application directly (Mac and Windows only) git clone https://github.com/ohmplatform/FreedomGPT.git freedom-gpt cd freedom-gpt yarn install yarn start:prod Build from source (Windows) cd alpaca.cpp cmake . cmake –build . –config
Compass Unified Parser is designed to convert models of various frameworks into a floating-point intermediate representation (IR). This IR is a standard IR designed by ARM China for the neural network compilation of the Zhouyi series. device. Parser’s processing flow and design philosophy The main goal of Parser is to convert a trained model into
Segmenot Anothe ythinog model(SAm)fromloseentercarryShowmiddleProducebornhighqualityquantityofthingbodymask,itCanbyuseComeforpicturepicturemiddleofPlacehavethingbodyProducebornmask.italreadythroughexistoneindivualDepend on 1100 Ten thousandopenpicturepictureand 11 100 millionindivualcovercoverGroupbecomeofnumberaccording tosetsuperiorEnterOKuptrainingpractice,andexisteachkindpointcutappointservicesmiddleToolhavepowerfulbigofsexable. installPack needwant Pthe ythono >= 3.8,byand Pthe yTorch >= 1.7 and TorchVithe siono >= 0.8.pleaseaccording toAccording tothisinsideofexplainbrightComeinstallPackPthe yTorchandTorchVithe sionothistwoindivualaccording torelyitem.ItheypowerfulstrongestablishdiscusssamehourinstallPackbranchholdCuD.AofPthe yTorchandTorchVithe siono. Install Segment Anything: pip install git+https://github.com/facebookresearch/segment-anything.git Or clone the repository locally and install git clone git@github.com:facebookresearch/segment-anything.git cd segment-anything; pip install -e
BELLE: Be Everyone’s Large Language model Engine (Open Source Chinese Dialogue Large Model) The goal of this project is to promote the development of the open source community of large Chinese dialogue models, and the vision is to be an LLM Engine that can help everyone. At this stage, this project is based on some
ChatYuan is a functional dialogue language model that supports Chinese and English bilinguals. ChatYuan-large-v2 uses the same technical solution as the v1 version, and has been optimized in terms of fine-tuning data, human feedback reinforcement learning, and chain of thought. ChatYuan-large-v2 is one of the models in the ChatYuan series that achieve high-quality results with
ChatDoctor is a medical chat model fine-tuned on the LLaMA model using medical domain knowledge. Note: This model has not yet reached 100% accurate output, please do not apply it to real clinical scenarios. Demo Page: https://huggingface.co/spaces/ChatDoctor/ChatDoctor training resource list 200k real dialogue between patients and doctors, source HealthCareMagic.com HealthCareMagic-200k. 26k real dialogue between patients
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
OPT-175B is Meta’s open source large language model with more than 175 billion parameters – comparable to GPT-3. The advantage of OPT-175B over GPT-3 is that it is completely free. Meta also publishes code repositories, development process logs, data, research papers, and other information related to OPT-175B. Although OPT-175B is free, Meta also gives some
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
LLaMA Homepage, Documentation and Downloads – Large Language Model – News Fast Delivery Read More »
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
RWKV is a language model that combines RNN and Transformer. It is suitable for long texts, runs faster, has better fitting performance, occupies less video memory, and takes less time for training. The overall structure of RWKV still adopts the idea of Transformer Block, and its overall structure is shown in the figure: Compared with
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
