Introduction Generative AI continues to grow in popularity but the infrastructure required to support these models is still under active development. Install (Amazon Linux 2 comes pre-installed with AWS CLI) and configure the AWS CLI for your region. Llama 2 is a collection of pre-trained and fine-tuned generative Sep 14, 2023 · Deploy to an endpoint. Variations Code Llama comes in three model sizes, and three variants: Code Llama: base models designed for general code synthesis and understanding; Code Llama - Python: designed specifically for Python; Code Llama - Instruct: for instruction following and safer deployment; All variants are available in sizes of 7B, 13B and 34B parameters. Aug 15, 2023 · Email to download Meta’s model. For max throughput, 13B Llama 2 reached 296 tokens/sec on ml. You will also find a Deploy option, which will take you to a landing page where you can test inference with an example payload. Code Llama is a model for generating and discussing code, built on top of Llama 2. Curator. Click Save. Note: On the first run, it may take a while for the model to be downloaded to the /models directory. Navigate to the Model Tab in the Text Generation WebUI and Download it: Open Oobabooga's Text Generation WebUI in your web browser, and click on the "Model" tab. Then enter in command prompt: pip install quant_cuda-0. To deploy meta-llama/Llama-2-13b-chat-hf to Amazon SageMaker you create a HuggingFaceModel model class and define our endpoint configuration including the hf_model_id, instance_type etc. git Access the directory and execute the download script: cd llama # Make the . Additionally, you can deploy the Meta Llama models directly from Hugging Face on top of cloud platforms Jun 10, 2024 · Search for Code Llama 70B In the JumpStart model hub, search for Code Llama 70B in the search bar. Aug 4, 2023 · Overall, LLMs make specialized knowledge more accessible to non-technical users through human-like interaction. Today, Meta Platforms, Inc. g… Feb 8, 2024 · Step 2: Configure AWS CLI. Additionally, you can deploy the Meta Llama models directly from Hugging Face on top of cloud platforms D:\Users\xxx\anaconda3\envs\llama\lib\site-packages\torch\distributed\launch. entrypoints. Alternatively, you can deploy Llama 2 via code using a Colab Notebook, which also contains instructions on adapter tuning, RLHF, and content Variations Code Llama comes in three model sizes, and three variants: Code Llama: base models designed for general code synthesis and understanding; Code Llama - Python: designed specifically for Python; Code Llama - Instruct: for instruction following and safer deployment; All variants are available in sizes of 7B, 13B and 34B parameters. It offers a more straightforward approach, reducing the complexities often faced during manual setups. Build an AI chatbot with both Mistral 7B and Llama2 using LangChain. Jul 18, 2023 · Readme. 0-cp310-cp310-win_amd64. Copy Model Path. While our customers loved this experience, we heard that deploying model Llama 3 is an accessible, open-source large language model (LLM) designed for developers, researchers, and businesses to build, experiment, and responsibly scale their generative AI ideas. Llama 2 foundation chat models are now available in the Databricks Marketplace for fine-tuning and deployment on private model serving endpoints. py:180: FutureWarning: The module torch. You should see the Code Llama 70B model listed under the Models category. Links to other models can be found in the Dec 4, 2023 · Step 3: Deploy. You will use a g5. 21 per 1M tokens. Meta-Llama-3-8b: Base 8B model. Part of a foundational system, it serves as a bedrock for innovation in the global community. You will need a node with about 10GB pvc and 16vCPU to get reasonable response time. If you are on Windows: Aug 3, 2023 · This article provides a brief instruction on how to run even latest llama models in a very simple way. This model was contributed by zphang with contributions from BlackSamorez. Section — 1: Deploy model on AWS Sagemaker. 本地部署 LLaMA 模型的方法. Read our research paper This release includes model weights and starting code for pre-trained and fine-tuned Llama language models — ranging from 7B to 70B parameters. Aug 21, 2023 · Deploy A Model. 8x higher request throughput than vLLM, by introducing key features like persistent batch (a. For LLaMA 3 70B: Code Llama. There are no ads or subscriptions required to use the Mar 18, 2024 · No-code fine-tuning via the SageMaker Studio UI. However, with most companies, it is too expensive to invest in the Apr 18, 2024 · The Llama 3 release introduces 4 new open LLM models by Meta based on the Llama 2 architecture. As of October 2023, TGI has been optimized for Code Llama, Mistral, StarCoder, and Llama 2 on NVIDIA A100, A10G and T4 GPUs. 4. Each model is wrapped in MLflow and saved within Unity Catalog, making it easy to use the MLflow evaluation in notebooks Instructions to download and run the NVIDIA-optimized models on your local and cloud environments are provided under the Docker tab on each model page in the NVIDIA API catalog, which includes Llama 3 70B Instruct and Llama 3 8B Instruct. Contribute to Ce-daros/LLaMa-Deploy development by creating an account on GitHub. Meta has officially announced its web-based chatbot. Oct 17, 2023 · This repository contains all the necessary code to deploy the deep learning model for Llama 2 inference. Jan 9, 2024 · For this post, we deploy the Llama 2 Chat model meta-llama/Llama-2-13b-chat-hf on SageMaker for real-time inferencing with response streaming. In the Environments tab, click on the name of the dev environment to enter its view. On this page. Activate it with: conda activate code-llama-env. 2xlarge delivers 71 tokens/sec at an hourly cost of $1. Instructions to download and run the NVIDIA-optimized models on your local and cloud environments are provided under the Docker tab on each model page in the NVIDIA API catalog, which includes Llama 3 70B Instruct and Llama 3 8B Instruct. We'll wal Jul 19, 2023 · Step 3: Deploy Llama 2 using Google Kubernetes Engine (GKE) Now that we have a docker image with Llama, we can deploy it to GKE. yml file defines the configuration for deploying the Llama ML model in a Docker container. Key components include: Build Context and Dockerfile: Specifies the build context and Dockerfile for the Docker image. Mar 7, 2023 · It does not matter where you put the file, you just have to install it. whl file in there. 1. Access Model Garden: Navigate to “Model Feb 2, 2024 · This GPU, with its 24 GB of memory, suffices for running a Llama model. Jul 18, 2023 · October 2023: This post was reviewed and updated with support for finetuning. Jul 18, 2023 · Llama 2 is a family of state-of-the-art open-access large language models released by Meta today, and we’re excited to fully support the launch with comprehensive integration in Hugging Face. Modified. Click File, select the New dropdown, and create a new Notebook. In this section, initialize the Llama-2-70b-chat-hf fine-tuned model with 4-bit and 16-bit precision as described in the following steps. Running a large language model normally needs a large memory of GPU with a strong CPU, for example, it is about 280GB VRAM for a 70B model, or 28GB VRAM for a 7B model for a normal LLMs (use 32bits for each parameter). Calling the llama3 large model via Python code: Ollama is a tool designed for the rapid deployment and operation of large language models such as Llama 3. Aug 24, 2023 · "Before deploying any applications of Code Llama, developers should perform safety testing and tuning tailored to their specific applications of the model. Code Llama is state-of-the-art for LLMs on code tasks and has the potential to make workflows faster and more efficient for current developers and lower the barrier to entry for people who are learning to code. Here we will demonstrate how to deploy a llama. Dec 13, 2023 · Deploying Llama 2. You will find listings of over 350 models ranging from open source and proprietary models. Code Llama is a model released by Meta that is built on top of Llama 2. Download a model e. These advanced models excel in various tasks, including code generation, code completion, infilling, instruction-based code generation and debugging. Click and navigate to the “Vertex AI” service. This state-of-the-art model is designed to improve productivity for programming tasks for developers by helping them create high-quality, well-documented code. Jun 18, 2024 · Figure 2: Llama 3 8B compared with Llama 2 models across various use case evaluations, including Chat, Code Generation, Summarization, and Retrieval Augmented Generation. Code Llama is an LLM capable of generating code, and natural language about code, from both code and natural language prompts. * CodeLlama models were used instead of Llama 2 due to the Llama 2 models' poor baseline performance on code generation tasks. Jul 21, 2023 · To set up a cloud environment, deploy using the Streamlit Community Cloud with the help of the Streamlit app template (read more here). We first introduce how to create Deploy fine tuned llama on SageMkaer: We use Large Model Inference/LMI container to deploy llama on SageMaker. Deploy Llama 2 to Amazon SageMaker. You can choose the model card to view details about the model such as license, data used to train, and how to use. For more detailed examples leveraging Hugging Face, see llama-recipes. You can also find two buttons, Deploy and Open notebook, which help you use the model using this no-code Explore the intricacies of model inference, code completion, and encoding with insights from "小窗幽记机器学习". Dec 22, 2023 · Creating the code-llama-env. LMDeploy is a toolkit for compressing, deploying, and serving LLM, developed by the MMRazor and MMDeploy teams. Note: The default configuration assumes your AWS account has a default VPC in the corresponding region. Oct 14, 2023 · Text Generation Inference (TGI) is an open-source toolkit for deploying and serving LLMs. Also, the demo code can perform the server side batch in order to improve the throughput. Code Generation. This model is designed for general code synthesis and understanding. Code Llama comes in three models: 7Billion, 13B, and 34B parameter versions. Choose llama-2 in the Template option. Use the Panel chat interface to build an AI chatbot with Mistral 7B. Code Llama is free for research and commercial use. Nov 1, 2023 · A step-by-step python tutorial on deploying Code-llama as a REST API service using Cog and Runpod. Mar 7, 2024 · Deploy Llama on your local machine and create a Chatbot. When it comes to deploying models on SageMaker endpoints, you can containerize the models using specialized AWS Deep Learning Container (DLC) images available for popular open source libraries. Aug 27, 2023 · Only OpenLlama, a reproduction of Llama 1, is available in Model garden, with code samples for deployment and tuning in Vertex AI. Amazon EC2 Inf2 instances, powered by AWS Inferentia2, now support training and inference of Llama 2 models. Before we get started, you will need to install panel==1. Deploy the Model Select the Code Llama 70B model, and then choose Deploy. In this example, we're going to deploy Llama-2-7b-chat, which is more suited for chat interactions. 0. The llama. We’ll need to open up the Google Cloud dashboard to Google Kubernetes Engine and create a new Standard Kubernetes Cluster named gpu-cluster. Deploying Through Code. The Dockerfile will creates a Docker image that starts a Nov 13, 2023 · Code Llama models are fine-tuned for programming tasks. Deploy the Llama-2-13b model with SageMaker Jumpstart. Aug 29, 2023 · Code Llama – Python: Given the prominence of Python in the AI and coding community, this variant has been further trained on a massive 100B tokens of Python code. However, to run the larger 65B model, a dual GPU setup is necessary. Llama 2 is being released with a very permissive community license and is available for commercial use. However, Perplexity Labs has deployed it on their server, allowing interested users to test Meta’s code on their platforms. I chose TheBloke/Llama-2–7B-GGML for this example since it has a good collection of quantized Llama 2 models, but other models could be used Apr 24, 2024 · The process of optimizing, accelerating inference, and deploying the Llama-3–8B-Instruct to AI PC includes the following specific steps, using the llm-chatbot code example from our commonly used This guide provides information and resources to help you set up Llama including how to access the model, hosting, how-to and integration guides. Code Llama. cd llama. Oct 29, 2023 · Afterwards you can build and run the Docker container with: docker build -t llama-cpu-server . Clone the model from HuggingFace. com:facebookresearch/llama. #kaggle #vertexai #llama2 #code Meta Llama 3. First we’ll need to deploy an LLM. It is designed for fast inference and high throughput, enabling you to provide a highly concurrent, low latency experience. As of October 2023, it supports Code Llama, Mistral, StarCoder, and Llama 2. The code of the implementation in Hugging Face is based on GPT-NeoX Discover how to download and serve Llama 2 models from Databricks Marketplace. Build the app. The prompt will now show (code-llama-env) – our cue we‘re inside! Code Llama is a code-specialized version of Llama 2 that was created by further training Llama 2 on its code-specific datasets, sampling more data from that same dataset for longer. Use VM. We provide a pre-built vLLM serving docker image. The 70B model is 131GB and requires a very powerful computer 😅. sh script to download the models using your custom URL /bin/bash . Getting started with Meta Llama. For cost-effective deployments, we found 13B Llama 2 with GPTQ on g5. 2 for the deployment. also, you can find sample code to load Code Llama models and run inference on GitHub. Alternatively, you can deploy via the example Instructions to download and run the NVIDIA-optimized models on your local and cloud environments are provided under the Docker tab on each model page in the NVIDIA API catalog, which includes Llama 3 70B Instruct and Llama 3 8B Instruct. Additionally, you will find supplemental materials to further assist you while building with Llama. /download script executable sudo chmod +x . The Llama 2 family of large language models (LLMs) is a collection of pre-trained and fine-tuned generative […] Jan 17, 2024 · You will be able to view the Llama 2 Neuron models on this page. Large Language Models. Nov 17, 2023 · Use the Mistral 7B model. Enter a resource name, e. Follow the steps in this GitHub sample to save the model to the model catalog. It . The following code snippet shows the simpler mode of deployment: Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 34 billion parameters. , my-llama-2. g5. 12xlarge instance type, which has 4 NVIDIA A10G GPUs and 96GB of GPU memory. You can easily call the Vertex AI SDK API to deploy models using the docker image: Oct 26, 2023 · Beginner-Friendly: For those new to AWS or Llama 2 deployment, a pre-configured setup can be a lifesaver. Click the New Resource button. cat > values. cpp server on a AWS instance for serving quantum and full-precision F16 models to multiple clients efficiently. Now follow the steps in the Deploy Llama 2 in OCI Data Science to deploy the model. api_server \ --model meta-llama/Meta-Llama-3-8B-Instruct. Since the Meta Code LlaMA project is open-source, you can deploy it on your server. May 24, 2024 · Deploying Ollama with CPU. Navigate to the llama repository in the terminal. They come in two sizes: 8B and 70B parameters, each with base (pre-trained) and instruct-tuned versions. 3. MetaAI recently introduced Code Llama, a refined version of Llama2 tailored to assist with code-related tasks such as writing, testing, explaining, or completing code segments Jul 22, 2023 · Firstly, you’ll need access to the models. Nov 15, 2023 · Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 34 billion parameters. Performance and Cost Efficiency Aug 25, 2023 · It is divided into two sections. whl. Code Llama is built on top of Llama 2 and is available in three models: Code Llama, the foundational code model; Codel Llama - Python specialized for To run Code Llama 7B, 13B or 34B models, replace 7b with code-7b, code-13b or code-34b respectively. Fire up VS Code and open the terminal. This creates a Conda environment called code-llama-env running Python 3. N. Aug 7, 2023 · 4. A10. sh # Run the . It’s designed to make workflows faster and efficient for developers and make it easier for people to learn how to code. Feb 16, 2024 · In this post, we walk through how to discover and deploy the Code Llama model via SageMaker JumpStart. Today, we are excited to announce that Llama 2 foundation models developed by Meta are available for customers through Amazon SageMaker JumpStart to fine-tune and deploy. You can choose the model card to view details about the model such as license, data used to train, and how to use it. 10. You can request this by visiting the following link: Llama 2 — Meta AI, after the registration you will get access to the Hugging Face repository Variations Code Llama comes in four model sizes, and three variants: Code Llama: base models designed for general code synthesis and understanding; Code Llama - Python: designed specifically for Python; Code Llama - Instruct: for instruction following and safer deployment; All variants are available in sizes of 7B, 13B, 34B, and 70B parameters. txt file to your GitHub repo and include the following prerequisite libraries: streamlit replicate 3. Navigate to the Llama2 repository and download the code: # Clone the code git clone git@github. Deploying here enables you to use SageMaker’s managed service capabilitiess like autoscaling, health checks, and model monitoring. k. launch is deprecated and will be removed in future. We achieve this for the LLaMA-2 7B model by combining the SparseGPT one-shot Oct 25, 2023 · An example of deploying the OpenLLaMA models to Vertex AI with vLLM serving can be accessed here. Search for Code Llama models. yaml <<EOF. openai. There is a notebook that shows how to use Sagemaker for LLM hosting here. To begin, start the server: For LLaMA 3 8B: python -m vllm. continuous batching), blocked KV cache Dec 20, 2023 · You can select from a variety of Llama model variants, including Llama Guard, Llama-2, and Code Llama. Note that you need docker installed on your machine. (The code is suitable for the case which is single sample/prompt per client request) Fine tune llama by deepspeed on SageMaker multiple nodes: We Aug 17, 2023 · In this tutorial video, I'll show you how to effortlessly deploy Llama2 large language model on AWS SageMaker using Deep Learning Containers (DLC). Enable the Use Template option. March 18, 2024. To start fine-tuning your Llama models using SageMaker Studio, complete the following steps: On the SageMaker Studio console, choose JumpStart in the navigation pane. We are unlocking the power of large language models. We introduce a novel approach to create accurate, sparse foundational versions of performant LLMs that achieve full accuracy recovery for fine-tuning tasks at up to 70% sparsity. Stable Diffusion AI Art (Stable Diffusion XL) In this article, we’ll explore how to deploy a Chat-UI and Llama model on Amazon EC2 for your own customized HuggingChat experience using open May 2, 2024 · There are two ways to deploy Meta Llama 3 on AWS Inferentia and Trainium based instances using the SageMaker JumpStart SDK. If you are an experienced researcher/developer, you can submit a request to download the models directly from Meta. Meta. Next, we need to clone the HuggingFace repo with the model. GPU. UPDATE August 30th, 2023: as announced in Cloud Next23 event Variations Code Llama comes in three model sizes, and three variants: Code Llama: base models designed for general code synthesis and understanding; Code Llama - Python: designed specifically for Python; Code Llama - Instruct: for instruction following and safer deployment; All variants are available in sizes of 7B, 13B and 34B parameters. Microsoft has opened up flood gates by joining hands with Meta by offering Meta’s open source Large Language Models (LLM) Llama 2 on Azure! Believe it or not, this is a big deal. Oct 15, 2023 · Oct 15, 2023. Enter an endpoint name (or keep the default value) and select the target instance type (for example Aug 28, 2023 · How to Use Metacode LLaMA. 3, ctransformers, and langchain. 12xlarge at $2. Then run: conda create -n code-llama-env python=3. Based on various benchmarks and human evaluations, Llama-2-Chat models offer comparable performance to popular closed-source models like ChatGPT and PaLM. All the variants can be run on various types of consumer hardware and have a context length of 8K tokens. On the main menu bar, click Kernel, and select Restart and Clear Outputs of All Cells to free up the GPU memory. In this post, we show low-latency and cost-effective inference of Llama-2 models on Amazon EC2 Inf2 instances using the latest AWS Neuron SDK release. To stop LlamaGPT, do Ctrl + C in Terminal. Resources. Meta Code LlamaLLM capable of generating code, and natural Code Llama is a code-specialized large-language model (LLM) that includes three specific prompting models as well as language-specific variations. The Llama-2-Chat variants are specifically optimized for dialogue use cases and they demonstrate significant performance improvements over other open-source chat models. More parameters mean greater complexity and capability but require higher computational power. Any LLM with an accessible REST endpoint would fit into a RAG pipeline, but we’ll be working with Llama 2 7B as it’s publicly available Nov 26, 2023 · Description. Note that --use_env is set by default in torchrun. 55. a. " Despite the risks, Meta places minimal Aug 24, 2023 · Code Llama is a state-of-the-art LLM capable of generating code, and natural language about code, from both code and natural language prompts. Here are simple steps that you can try Llama 13B, by few clicks on Kubernetes. distributed. Apr 23, 2024 · We are now looking to initiate an appropriate inference server capable of managing numerous requests and executing simultaneous inferences. Deploy via UI: By selecting “Deploy” and agreeing to the terms, you can initiate the deployment process directly. Description. This means even those with minimal AWS knowledge can deploy Llama 2 confidently. Copy the Model Path from Hugging Face: Head over to the Llama 2 model page on Hugging Face, and copy the model path. Oct 4, 2023 · Recently, Llama 2 was released and has attracted a lot of interest from the machine learning community. Jul 19, 2023 · Llama 2 is the newest open-sourced LLM with a custom commercial license by Meta. Section — 2: Run as an API in your application. The Llama 2 chatbot app uses a total of 77 lines of code to build: Introduction. But since your command prompt is already navigated to the GTPQ-for-LLaMa folder you might as well place the . In this tutorial we will walk you through the process of how to deploy Llama2 model on Azure Machine Learning studio. Deploying Llama 2 and Code Llama follows similar steps. This repository is intended as a minimal example to load Llama 2 models and run inference. We release all our models to the research community. Build an AI chatbot with both Mistral 7B and Llama2. /download script . 2. Deploying a model to the cloud is a simple process with sych-llm-playground. sh Aug 8, 2023 · 1. Use aws configure and omit the access key and secret access key if Aug 24, 2023 · Despite the risks, Meta places minimal restrictions on how developers can deploy Code Llama, whether for commercial or research use cases. This is the repository for the 34B instruct-tuned version in the Hugging Face Transformers format. For instance, one can use an RTX 3090, an ExLlamaV2 model loader, and a 4-bit quantized LLaMA or Llama-2 30B model, achieving approximately 30 to 40 tokens per second, which is huge. You may also see lots of output like this for a few minutes, which is normal: Jan 29, 2024 · code - The base model for code completion; Download from Meta. Amazon’s AWS released Amazon SageMaker Jumpstart end of last year which is a similar offer to Azure to support deploying open source models for Variations Code Llama comes in three model sizes, and three variants: Code Llama: base models designed for general code synthesis and understanding; Code Llama - Python: designed specifically for Python; Code Llama - Instruct: for instruction following and safer deployment; All variants are available in sizes of 7B, 13B and 34B parameters. Use torchrun. Our latest version of Llama is now accessible to individuals, creators, researchers, and businesses of all sizes so that they can experiment, innovate, and scale their ideas responsibly. docker run -p 5000:5000 llama-cpu-server. Let’s save the model to the model catalog, which makes it easier to deploy the model. Oct 4, 2023 · Deploying Code Llama Models. This release includes model weights and starting code for pre-trained and instruction-tuned Sep 25, 2023 · Access Vertex AI: Once your account is set up search “Vertex AI” in the search bar at the top. Set the zone to us-central1-c. , releases Code Llama to the public, based on Llama 2 to provide state-of-the-art performance among open models, infilling capabilities, support for large input contexts, and zero-shot instruction following ability for programming tasks. Additionally, you can deploy the Meta Llama models directly from Hugging Face on top of cloud platforms In particular, LLaMA-13B outperforms GPT-3 (175B) on most benchmarks, and LLaMA-65B is competitive with the best models, Chinchilla-70B and PaLM-540B. Llama in a Container allows you to customize your environment by modifying the following environment variables in the Dockerfile: HUGGINGFACEHUB_API_TOKEN: Your Hugging Face Hub API token (required). Add a requirements. B. g. It has the following core features: Efficient Inference: LMDeploy delivers up to 1. Add stream completion. Essentially, Code Llama features enhanced coding capabilities. It can generate both code and natural language about code. Simplicity at its Best: Enjoy a Hassle-Free Experience May 1, 2024 · This article, with code snippets and explanations, outlines a detailed pathway to adapting, fine-tuning, and deploying LLaMA-3, preparing developers to handle advanced NLP tasks efficiently Feb 8, 2024 · With Code Llama 70B models, developers now have access to tools that significantly enhance the quality of output, thereby driving productivity in professional software development. Nov 15, 2023 · Last summer, we announced the availability of Llama 2 on Azure earlier this summer in the model catalog in Azure Machine Learning, with turn-key support for operationalizing Llama 2 without the hassle of managing deployment code or infrastructure in your Azure environment. /download. cpp project offers unique ways of utilizing cloud computing resources. sh Sep 26, 2023 · In this benchmark, we tested 60 configurations of Llama 2 on Amazon SageMaker. By leveraging Streamlit’s extensive library of community code snippets, you can even deploy a LLaMa model and get it to write improvements to its own front-end code. Nov 26, 2023 · The docker-compose. Code Llama is now available on Ollama to try! This video shows you step by step instructions as how to deploy and run Llama 2 and Code Llama models on GCP in Vertex AI API. By running the deploy command, you can select your cloud provider, in this case, AWS, and choose the model you'd like to deploy. 5. Sep 5, 2023 · Sep 5, 2023. They must simply agree not to use the model for malicious Aug 24, 2023 · Run Code Llama locally August 24, 2023. You can deploy the model with two lines of code for simplicity, or focus on having more control of the deployment configurations. May 6, 2024 · Large language models (LLMs) have revolutionized Natural Language Processing (NLP), but their size creates computational bottlenecks. Run the download. The code, pretrained models, and fine-tuned Sep 20, 2023 · 3. HF_REPO: The Hugging Face model repository (default: TheBloke/Llama-2-13B-chat-GGML). ng yq id kx tb ji jn bh rz mt