Mlc llm flutter github. md at main · mlc-ai/mlc-llm 🦜️🔗 LangChain.

Mlc llm flutter github For example: mlc_ai_cu122-0. build inspite of properly configured pipeline. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. Enjoy private, server-free, seamless AI conversations. a: sentencepiece static library; libtokenizers_cpp. Halide: Part of TVM's TIR and arithmetic simplification module originates from Halide. I finetuned with dataset containing data like {"text": "[INST] Query: Search for action movies of the lawyer f You signed in with another tab or window. Chat with AI large language models running natively in your browser. MLC LLM is a universal solution that allows any language model to be deployed natively on a diverse set of hardware backends and native applications, plus a productive framework for everyone to further optimize model performance for their own use cases. - OmniQuant/runing_quantized_models_with_mlc_llm. Please note that WebLLM Assistant is in the early stages of General Questions How do I get the eagle and medusa mode of the LLM model? I try to do the "convert_weight", "gen_config", and "compile" steps of MLC-LLM with the addition --model-type "eagle" or "medusa" on the command line. Machine Learning Compilation for Large Language Models (MLC LLM) is a high-performance universal deployment solution that allows native deployment of any large language models with native APIs with compiler acceleration. model points to the Hugging Face repository which contains the pre-converted model weights. model lib:模型库是指能够执行特定模型架构的可执行库。在 Linux 上,这些库文件的后缀为 . com/mlc-ai/mlc Machine Learning Compilation for Large Language Models (MLC LLM) is a high-performance universal deployment solution that allows native deployment of any large language models with native APIs with compiler acceleration. This will tell the SDK which agent to use for your interactions. Universal LLM Deployment Engine with ML Compilation - mlc-llm/docs/README. The mission of this project is to enable everyone to develop, optimize and deploy AI models natively on everyone's devices You signed in with another tab or window. Our mission is to enable everyone to develop, optimize High-performance In-browser LLM Inference Engine . Find and fix vulnerabilities Actions. Universal LLM Deployment Engine with ML Compilation - mlc-llm/README. Already have an account? General Questions. use your own models, extend the API, etc. The Problem. Documentation | Blog | Discord \n. RedPajama-INCITE-Chat-3B-v1-q4f16_1-MLC. 0 Get Started. gitmodules at main · mlc-ai/mlc-llm Universal LLM Deployment Engine with ML Compilation - Pull requests · mlc-ai/mlc-llm Documentation | Blog | Discord. co/mlc-ai Available quantization codes are: q3f16_0, q4f16_1, q4f16_2, q4f32_0, q0f32, and q0f16. To compile and use your own models with WebLLM, please check out MLC LLM document on how to compile and deploy new model weights and libraries to WebLLM. it didn't work on my device too. lang. You switched accounts on another tab or window. md at main · mlc-ai/mlc-llm WebLLM: High-Performance In-Browser LLM Inference Engine. Model Conversion For model conversion, we primarily refer to this tutorial: https Contribute to mlc-ai/notebooks development by creating an account on GitHub. High-performance In-browser LLM Inference Engine . The gemma_flutter library leverages Mediapipe, which significantly benefits from GPU acceleration. Here, we go over the high-level idea. Contribute to cfahlgren1/webllm-playground development by creating an account on GitHub. With that being said, once you are ready, feel free to open a PR for both the TVM side and the mlc-llm side (old workflow is fine), then @davidpissarra and/or I will 🐛 Bug Using @junrushao 's #1530 (comment), but with additional patches to enable opencl, the generation quality for TinyLlama is surprisingly bad. This page focuses on the second purpose. We learned a lot from the following projects when building TVM. The Python API is a part of the MLC-LLM package, which we have prepared pre-built pip Universal LLM Deployment Engine with ML Compilation - mlc-llm/android/README. Run LLMs in the Browser Contribute to wuzhiping/mlc-llm development by creating an account on GitHub. dart is an unofficial Dart port of the popular LangChain Python framework created by Harrison Chase. Already have an account? You signed in with another tab or window. a: the cpp binding implementation; If you are using an IDE, you can likely first use cmake to generate these libraries and add them to your development environment. About. ipynb at main · OpenGVLab/OmniQuant The cuda version is after the cu part of the wheel name The python version is after the cp part of the wheel name. ) Your product does have poor or no internet access (military, IoT, edge, extreme environment, etc. Download pre-quantized weights. cc. Contribute to ego/datasette-llm-mlc development by creating an account on GitHub. Contribute to mlc-ai/web-llm development by creating an account on GitHub. ai/wheels mlc-llm-nightly-cpu mlc-ai-nightly-cpu Is there no stable version that is re Contribute to googlebleh/mlc-llm-docker development by creating an account on GitHub. in the mlc-llm directory to install the mlc_llm package. Machine Learning Containers for NVIDIA Jetson and JetPack-L4T - dusty-nv/jetson-containers Universal LLM Deployment Engine with ML Compilation - mlc-ai/mlc-llm Contribute to hfyydd/mlc-llm-chat-python development by creating an account on GitHub. build --model . mm: https://github. \nEverything runs locally with no server support and accelerated with local GPUs on Based on experimenting with GPTQ-for-LLaMa, int4 quantization seems to introduce 3-5% drop in perplexity, while int8 is almost identical to fp16. Some examples of devices including MLC: LSM6DSOX, LSM6DSRX, ISM330DHCX, IIS2ICLX, LSM6DSO32X, ASM330LHHX Contribute to mlc-ai/binary-mlc-llm-libs development by creating an account on GitHub. We also learned and adapted some part of High-performance In-browser LLM Inference Engine . Specifically, we add RedPjama-INCITE WebLLM Assistant brings the power of AI agent directly to your browser! Powered by WebGPU, WebLLM Assistant runs completely inside your browser and ensures 100% data privacy while providing seamless AI assistance as you browse the internet. 7B-Instruct-q4f16_1-MLC as its a pretty small download and I've found it runs decent. for testing I will be using SmolLM-1. Hi, I implemented a customized tokenizer, which optimized some segmentation logics, and use it trained my model. Universal LLM Deployment Engine with ML Compilation - mlc-ai/mlc-llm github-project-automation bot moved this to Done in MLC LLM Model Request Tracking Feb 23, 2024 Sign up for free to join this conversation on GitHub . )This page walks us through the process of adding a model variant with mlc_llm convert_weight, which takes a huggingface model as input and converts/quantizes into MLC-compatible weights. 0 Contribute to mlc-ai/llm-perf-bench development by creating an account on GitHub. cc, llm_chat. Our mission is to enable everyone to develop, optimize Step 2. If I want to use them now, are there any corresponding instructions? I couldn't find the relevant section at https://llm. One specific issue this thread aims to address is the massive duplication between two subcommands: mlc_chat compile and mlc_chat gen_mlc_chat_config In-Browser Inference: WebLLM is a high-performance, in-browser language model inference engine that leverages WebGPU for hardware acceleration, enabling powerful LLM operations directly within web browsers without server-side processing. The mission of this project is to enable everyone to develop, optimize and deploy AI models natively on everyone's devices Github; Discord Server; Other Resources MLC Course; MLC Blog; Web LLM; Other Resources MLC Course; MLC Blog; Web LLM; 0. Enable everyone to develop, optimize and deploy AI models natively on everyone's devices. Quick Start To begin with, try out MLC LLM support for int4-quantized Llama3 8B. They trained and finetuned the Mistral base models for chat to create the OpenHermes series of models. Saved searches Use saved searches to filter your results more quickly You signed in with another tab or window. ) You work in a data-sensitive environment (healthcare, IoT, military, law, etc. Universal LLM Deployment Engine with ML Compilation - mlc-ai/mlc-llm General Questions Hi, I am deploying my own quantization methods in MLC-LLM, but get errors about running TVM Dlight low-level optimizations. By the end of this guide, you will have a fully functional LLM running locally on your machine. Notifications You must be signed in to change notification New issue Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the 🐛 Bug I'm trying to replicate the LLaMA example method as mentioned in introduction documentation gives errors related to relax. Universal LLM Deployment Engine with ML Compilation - mlc-ai/mlc-llm During the compilation, you'll also need to install Rust. server? (fwiw: the md5 hash based scheme tying the weights and generated lib as one "logical whole" is ingenious but does cause some problem when I need to try and find the MLC LLM is a machine learning compiler and high-performance deployment engine specifically designed for large language models. /chatglm2-6b" for model "chat Skip to content. But when run mlc-llm on Intel Arc DGPU. This page introduces how to use the engines in MLC LLM. Instant dev environments High-performance In-browser LLM Inference Engine . As long as user complies with the conditions stated in License Document , user may use the Software for free of charge, but the Software is basically paid software. where MODEL is the model folder after compiling with :ref:`MLC-LLM build process <compile-model-libraries>`. dart? # LangChain. Its mission is to enable everyone to develop, optimize, and deploy AI models natively on their platforms. a: the c binding to tokenizers rust library; libsentencepice. The mission of this project is to enable everyone to develop, optimize and deploy AI models natively on everyone's devices This guide provides step-by-step instructions for running a local language model (LLM) i. This step MLC LLM compiles and runs code on MLCEngine -- a unified high-performance LLM inference engine across the above platforms. Sign in Product GitHub Copilot. Write better code with AI Security. - GitHub - Mobile-Artificial-Intelligence/maid: Maid is a cross-platform Flutter app for interfacing with GGUF / llama. So why mlc-llm cannot lowering to hexagon target codes? Is there anything unsupported on the way of "Relax-->TIR-->hexagon target codes" ? 🐛 Bug Following the latest doc to install mlc_chat. WebLLM works as a companion project of MLC LLM and it supports custom models in MLC format. Run LLMs in the Browser with MLC / WebLLM . Python REST Server Command Line Web Browser iOS Android. General Questions I fine tuned LLaMA2 model using LoRA so that it can answer some questions related to media search queries. ; Mistral models via Nous Research. Recently, the mlc-llm team has been working on migrating to a new model compilation workflow, which we refer to as SLM. SLM is the new approach to bring modularized python first compilation to MLC, allowing users and developers to support new models and features more easily. To Reproduce Steps to reproduce the behavior: I am currently running llama 2 13b chat q8f16_1 on an A10G on huggingface and g WebLLM works as a companion project of MLC LLM and it supports custom models in MLC format. Documentation | Blog | Discord. MLC LLM compiles and runs code on MLCEngine -- a unified high-performance LLM inference engine across the above platforms. Hi guys! I'm testing the newly added StableLM-2 (1. The Android app will download model weights from the Hugging # automatically pull or build a compatible container image jetson-containers run $(autotag mlc) # or explicitly specify one of the container images above jetson-containers run dustynv/mlc:0. Saved searches Use saved searches to filter your results more quickly Saved searches Use saved searches to filter your results more quickly Universal LLM Deployment Engine with ML Compilation - mlc-llm/ios/README. Additionally, for model conversion and quantization, you should also execute pip install . cpp models locally, and with Ollama, Mistral, Google Gemini and OpenAI models remotely. ; Mobile vs. AsyncMLCEngine` which support full OpenAI API completeness for easy integration into other Python projects. rest from nightly build, the script will crash when started with a model (doing --help works fine) To Reproduce Steps to reproduce the behavior: create a new conda environment with pytho Overview PR #1098 takes the first stab at enabling simplistic testing in MLC LLM by starting from lints with the introduction of black (code formatter) and isort (import formatter). MLCEngine provides OpenAI-compatible API available Thanks to MLC, running such large models on your mobile devices is now possible. Initialize the class with your API key; Specify the ID of the agent you created earlier. mlc. You want to increase customization (e. Navigation Menu Sign up for a free GitHub account to open an issue and contact its maintainers and the community. e. \n\n MLC LLM \n. github-project-automation bot added this to MLC LLM Model Request Tracking Mar 26, 2024 Sign up for free to join this conversation on GitHub . Contribute to mlc-ai/binary-mlc-llm-libs development by creating an account on GitHub. json is required for both compile-time and runtime, hence serving two purposes:. Sign in Product Documentation | Blog | Discord. Shouldn't the path to the generated model be figured out automatically by serve. WebLLM Playground is built on top of MLC-LLM and WebLLM Chat. To install the MLC LLM Python package, you have two MLC LLM is a machine learning compiler and high-performance deployment engine for large language models. The mission of this project is to enable everyone to develop, optimize, and deploy AI models natively on everyone’s Love MLC, awesome performance, keep up the great work supporting the open-source local LLM community! That said, I basically shuck the mlc_chat API and load the TVM shared model MLC LLM generates performant code for WebGPU and WebAssembly, so that LLMs can be run locally in a web browser without server resources. To download and utilize some pre-comipled LLM models for mlc-llm we can visit the mlc-ai organization on huggingface https://huggingface. Universal LLM Deployment Engine with ML Compilation - mlc-ai/mlc-llm LLM plugin for running models using MLC. But it seems MLC-LLM only support one type of tokenizer in 3rdparty/tokenizers-cpp and the output of encode is really different from transformers. The mission of this project is to enable everyone to develop, optimize and deploy AI models natively on everyone's devices Therefore, the changes in lm_support. IllegalArgumentException: Failed requirement. The mission of this project is to enable everyone to develop, optimize and deploy AI models natively on everyone's devices mlc-chat-config. 1-cp311-cp311-manylinux_2_28_x86_64. To run a model with MLC LLM, we need to convert model weights into MLC format (e. Contribute to microsoft/MLC development by creating an account on GitHub. 6B) on MLC. The models to be built for the Android app are specified in MLCChat/mlc-package-config. Universal LLM Deployment Engine with ML Compilation - mlc-ai/mlc-llm mlc-ai / mlc-llm Public. /chatglm2-6b --target metal --quantization q4f16_1 Using path ". What is LangChain. To interact with MLC-compiled LLMs on iOS, the only file you need is LLMChat. MLC LLM supports directly loading real quantized models exported by AutoAWQ. whl Contribute to mlc-ai/mlc-zh development by creating an account on GitHub. [ICLR2024 spotlight] OmniQuant is a simple and powerful quantization technique for LLMs. Automate any workflow Codespaces. mlc-llm: Universal LLM Deployment Engine with ML Compilation: 19,086: Maid is a cross-platform Flutter app for interfacing with GGUF / llama. Chat Stats. @Hzfengsy im a liitle bit confused, cause TVM does have Hexagon backend codegen, and mlc-llm is based on TVM Unity. libtokenizers_c. There are some non-trivial amount of work to do to enab Saved searches Use saved searches to filter your results more quickly Overview As we have confirmed that the new CLI and JIT pipeline works, we are going to deprecate the old c++-based mlc_chat_cli, in favor of the new Python-based SLM CLI. Build LLM-powered Dart/Flutter applications. MLCEngine provides OpenAI-compatible API available through REST server, python, javascript, iOS, Android, all backed by the same engine and compiler that we keep improving with the community. runtime exception log : FATAL EXCEPTION: main Process: ai. Llama 3. ipynb General Question Your Website states: "It does not yet work on Google Pixel due to limited OpenCL support. Everything runs inside the browser with no server support and is accelerated with WebGPU. 1. md at main · mlc-ai/mlc-llm 🦜️🔗 LangChain. Once the compilation is complete, the chat program mlc_chat_cli provided by mlc-llm will be installed. In this Project Page | Documentation | Blog | WebLLM | WebStableDiffusion | Discord. Step 0: Clone the below repository on your local machine and upload the Llama3_on_Mobile. MLC LLM is a universal solution that allows any language models to be deployed natively on a diverse set of hardware backends and native applications, plus a MLC LLM is a universal solution that allows any language models to be deployed natively on a diverse set of hardware backends and native applications, plus a productive framework for everyone to further optimize model performance for their own use cases. Desktop: The response generation is noticeably faster on mobile devices equipped with a GPU compared to a non-GPU desktop environment. When I was building the Android SDK according to the official documentation, the 'mlc_llm package' command had difficulty downloading the model and always timed out for the connection, hoping to get some help:[2024-10-18 13:02:37] INFO d 参考自mlc-llm,个人尝试在android手机上部署大模型并运行. Skip to content. The tests/python tests mlc_chat. py may need to be migrated later when the new workflow is up. cpp models locally, and with Ollama and OpenAI models remotely. ) MLC LLM is a machine learning compiler and high-performance deployment engine for large language models. com/mlc-ai/mlc-llm/blob/main/cpp/llm_chat. Sign up for GitHub Hi @lucasjinreal as far as I am aware mlc doesn't have any direct comparisons with other tools, but I was able to find this comparison which shows at least some data between several tools (including mlc and vllm). WebLLM offers a minimalist and modular interface Contribute to mlc-ai/binary-mlc-llm-libs development by creating an account on GitHub. cc would not be affected; but those in relax_model and mlc_llm/core. Build Runtime and Model Libraries ¶. The mission of this project is to enable everyone to develop, optimize and You signed in with another tab or window. It is recommended to have at least 6GB free VRAM to run it. Explore Mlc-llm's capabilities with Flutter for seamless integration and enhanced performance in your applications. The mission of this project is to enable everyone to develop, optimize, and deploy AI models natively on everyone's platforms MLC LLM provides Python API through classes :class:`mlc_llm. Reload to refresh your session. Universal LLM Deployment Engine with ML Compilation - mlc-ai/mlc-llm @MasterJH5574 @vinx13 Hi MLC LLM's developers, I see that various speculative decoding algorithms such as small draft model, Medusa, and EAGLE have been implemented in MLC LLM. 0 # or if using 'docker run' (specify image and mounts/ect) sudo docker run --runtime nvidia -it --rm --network=host dustynv/mlc:0. @Kathryn-cat there is a C FFI but we can write iOS and Not sure if it's compatiable with flutter. The problem seems specific to TinyLlama; the same setup (using the same opencl patches) wo General Questions. @Nikhil34712 All reactions Maid is a cross-platform Flutter app for interfacing with GGUF / llama. - mlc-llm-AI/README. - Issues · mlc-ai/web-llm-chat. Since LLMC is seamlessly integrated with AutoAWQ, 🐛 Bug To Reproduce Steps to reproduce the behavior: 1. We will continue to bring support and welcome contributions from the open source communi MLC LLM \n. mlcchat, PID: 18049 java. You signed out in another tab or window. json: in the model_list, model points to the Hugging Face repository which. Future updates will include support for a broader range of foundational models. ailia LLM Flutter Package CAUTION !! “ailia” IS NOT OPEN SOURCE SOFTWARE (OSS). Stable LM 3B is the first LLM model that can handle RAG, using documents such as web pages to answer a query, on all devices. Navigation Menu Toggle navigation. md at main · mlc-ai/mlc-llm Ok, I only looked at this briefly, so hopefully I'm not steering anyone in the wrong direction. MLC LLM is a universal solution that allows any language models to be deployed natively on a diverse set of hardware backends and native applications, plus a productive framework for everyone to further optimize model performance for their own use cases. Information about other arguments can be found under :ref:`Launch the server <rest_launch_server>` section. | Project Page | Blog | WebLLM | WebStableDiffusion | Discord. From #1306 and mlc_chat code, I understand that its not going to test ml_llm/relax_model. 3 top-tier open models are in the fllama HuggingFace repo. It reuses the model artifact and builds the flow of MLC LLM. I've noticed that when using the same model in HF Transformers, one has the option to pass to the model not just the prompt but also the past key values, in which case the inference is accelerated enormously. Specify how we compile a model (shown in :ref:`compile-model-libraries`), and; Specify conversation behavior in runtime. The mission of this project is to enable everyone to deve Explore Mlc-llm's capabilities with Flutter for seamless integration and enhanced performance in your applications. Machine Learning Compilation for Large Language Models (MLC LLM) is a high-performance universal deployment solution that allows native deployment of any large language models with General Questions. This repository is crafted with reference to the implementations of mlc_llm and mlc_imp. MLCEngine` and :class:`mlc_llm. Vulkan drivers are installed properly and mlc_llm detects vulk 🐛 Bug The output of speculative decoding is inconsistent with the output of a single model Speculative decoding for Llama-2-7b-chat-hf-q0f32, the ssm is Llama-2-7b-chat-hf-q4f16: Prompt 0: What is the meaning of life? Contribute to cfahlgren1/webllm-playground development by creating an account on GitHub. GitHub Contribute to mlc-ai/relax development by creating an account on GitHub. md at main · saeedm64/mlc-llm-AI You signed in with another tab or window. Here is my QuantizedLinear forward code: def forward( because --model-lib-path is a required argument, I had to lookup the lib (by timestamp since I can't do md5 in my head). Our mission is to enable everyone to Import the LLMLabSDK into your project. LangChain provides a set of ready-to-use components for working with language models and a standard interface for chaining them together to formulate Section I: Quantize and convert original Llama-3–8B-Instruct model to MLC-compatible weights. 3. 15. We read every piece of feedback, and take your input very seriously. Contribute to biyuehuang/mlc-llm-for-Arc development by creating an account on GitHub. This blog offers you an end-to-end tutorial on quantizing, converting, and deploying the Llama3–8B-Instruction MLC LLM is a **universal solution** that allows **any language models** to be **deployed natively** on a diverse set of hardware backends and native applications, plus a **productive Documentation | Blog | Discord. Would it be possible to use int8 quantization with mlc-llm, assuming the model fits in VRAM Universal LLM Deployment Engine with ML Compilation - mlc-llm/LICENSE at main · mlc-ai/mlc-llm Is there a stable release? I noticed that the instruction for installing refers to a nightly build. md at main · mlc-ai/mlc-llm You signed in with another tab or window. Expected behavior Navigation Menu Toggle navigation. ai/docs/. Universal LLM Deployment Engine with ML Compilation - mlc-llm/. GitHub repository metrics, like number of stars, contributors, issues, releases, and time since last commit, have been collected as a proxy for popularity and active maintenance. It supports the conversion of models such as Llama, Gemma, and also LLaVA, and includes the necessary implementations for processing these models. For example, you can directly use commands such as mlc_llm gen_config and mlc_llm convert_weight to change the minicpm and minicpm_v models. Overview. You can find all the parameters that it uses here: Documentation | Blog | Discord. How | Project Page | Blog | WebLLM | WebStableDiffusion | Discord. But as far as I can tell you have to build new models yourself using the python build script. Project Page | Documentation | Blog | WebLLM | WebStableDiffusion | Discord. Contribute to guming3d/mlc-llm-android development by creating an account on GitHub. . I've used the MLCChat App, it showing the below models alone which is shown in the screenshot, how can I access my own models, which is in my device?; Is there any possible to use my local models in this MLCChat App ?; How can I do this with flutter? 🔗 Screenshot. I. Full OpenAI API Compatibility: Seamlessly integrate your app with WebLLM using OpenAI API with functionalities such as MLC LLM compiles and runs code on MLCEngine -- a unified high-performance LLM inference engine across the above platforms. You signed in with another tab or window. so,在 macOS 上,后缀 Actively moving towards the next-generation deployment pipeline in MLC LLM, before it is made public, we wanted to make sure the UX of our tooling being as user-friendly as possible. dart #. My questions are: Maid is an cross-platform free and open source application for interfacing with llama. g. Looking forward to your reply, thanks! You signed in with another tab or window. 🐛 Bug Hello, I am getting truncated responses (generation stops mid-sentence) while using the mlc-llm rest api. python -m mlc_llm. Model Selector. Universal LLM Deployment Engine with ML Compilation - mlc-ai/mlc-llm Universal LLM Deployment Engine with ML Compilation - mlc-ai/mlc-llm MLC中有一些自己定义的术语,我们通过了解这些基本术语,对后面的使用会提供很大的帮助。 modelweights:模型权重是一个文件夹,其中包含语言模型的量化神经网络权重以及分词器配置。. Meta Label Correction for Noisy Label Learning. Home Docs Github MLC LLM: Universal LLM Deployment Engine With ML Compilation. GPU Requirement: For best performance, especially in the web build, ensure the device has a GPU. cpp models locally High-performance In-browser LLM Inference Engine . WebLLM is a high-performance in-browser LLM inference engine that directly brings language model inference directly onto web browsers with hardware acceleration. examples and tools for the Machine Learning Core feature (MLC) available in STMicroelectronics MEMS sensors. 1 8B using Docker images of Ollama and OpenWebUI. Currently, the project generates three static libraries. The framework for autonomous intelligence Design intelligent agents that execute multi-step processes autonomously. General Questions I am new to this repo trying to understand things. Here's the interface to MLC's C++ API: https://github. Action Items Deprecate mlc_chat_cli, in favor of #1563 Update CLI Universal LLM Deployment Engine with ML Compilation - mlc-ai/mlc-llm MLC LLM compiles and runs code on MLCEngine -- a unified high-performance LLM inference engine across the above platforms. 1-r36. python -m pip install --pre -U -f https://mlc. Once you have launched the Server, you can use the API in your own program to send requests. jmcz juxee fxfty njout ebgkzn lgruqdxh pqnuaq yin bcmyw pgfkcn