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README.md
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- [🟢 How to use Yi?](#-how-to-use-yi)
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- [Quick start](#quick-start)
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- [Choose your path](#choose-your-parth)
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- [Fine tune](#fine-tune)
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- [Quantization](#quantization)
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- [Deployment](https://github.com/01-ai/Yi/blob/main/docs/deployment.md)
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- [Quick start](#quick-start)
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- [Choose your path](#choose-your-parth)
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- [Fine tune](#fine-tune)
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- [Quantization](#quantization)
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- [Deployment](https://github.com/01-ai/Yi/blob/main/docs/deployment.md)
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If you prefer to deploy Yi models locally,
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- 🙋♀️ and you have **sufficient** resources (for example, NVIDIA A800 80GB), you can choose one of the following methods:
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- [pip](#
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- [Docker](https://github.com/01-ai/Yi/blob/main/docs/README_legacy.md#11-docker)
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- [conda-lock](https://github.com/01-ai/Yi/blob/main/docs/README_legacy.md#12-local-development-environment)
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- [Yi-34B-Chat](https://platform.lingyiwanwu.com/) (Yi official beta)
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- Access is available through a whitelist. Welcome to apply (fill out a form in [English](https://cn.mikecrm.com/l91ODJf) or [Chinese](https://cn.mikecrm.com/gnEZjiQ)).
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This tutorial guides you through every step of running Yi (Yi-34B-Chat) locally and then performing inference.
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- This tutorial assumes you are running the **Yi-34B-Chat** with an **A800 (80G)** GPU.
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- For detailed deployment requirements to run Yi models, see [hardware requirements]( https://github.com/01-ai/Yi/blob/main/docs/deployment.md).
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- Make sure Python 3.10 or later version is installed.
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To set up the environment and install the required packages, execute the following command.
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pip install -r requirements.txt
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```
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You can download the weights and tokenizer of Yi models from the following sources:
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- [ModelScope](https://www.modelscope.cn/organization/01ai/)
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- [WiseModel](https://wisemodel.cn/organization/01.AI)
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You can perform inference with Yi chat or base models as below.
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1. Create a file named `quick_start.py` and copy the following content to it.
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Hello! How can I assist you today?
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```
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The steps are similar to [Run Yi chat model](#run-yi-chat-model).
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</details>
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### Finetuning
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```bash
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via applications. All usage must adhere to the [Yi Series Models Community License Agreement 2.1](https://github.com/01-ai/Yi/blob/main/MODEL_LICENSE_AGREEMENT.txt).
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For free commercial use, you only need to send an email to [get official commercial permission](https://www.lingyiwanwu.com/yi-license).
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<div align="right"> [ <a href="#building-the-next-generation-of-open-source-and-bilingual-llms">Back to top ⬆️ </a> ] </div>
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- [🟢 How to use Yi?](#-how-to-use-yi)
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- [Quick start](#quick-start)
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- [Choose your path](#choose-your-parth)
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- [pip](#pip)
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- [llama.cpp](https://github.com/01-ai/Yi/blob/main/docs/yi_llama.cpp.md)
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- [Web demo](#web-demo)
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- [Fine tune](#fine-tune)
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- [Quantization](#quantization)
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- [Deployment](https://github.com/01-ai/Yi/blob/main/docs/deployment.md)
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- [Quick start](#quick-start)
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- [Choose your path](#choose-your-parth)
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- [pip](#pip)
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- [llama.cpp](https://github.com/01-ai/Yi/blob/main/docs/yi_llama.cpp.md)
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- [Web demo](#web-demo)
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- [Fine tune](#fine-tune)
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- [Quantization](#quantization)
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- [Deployment](https://github.com/01-ai/Yi/blob/main/docs/deployment.md)
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If you prefer to deploy Yi models locally,
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- 🙋♀️ and you have **sufficient** resources (for example, NVIDIA A800 80GB), you can choose one of the following methods:
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- [pip](#pip)
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- [Docker](https://github.com/01-ai/Yi/blob/main/docs/README_legacy.md#11-docker)
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- [conda-lock](https://github.com/01-ai/Yi/blob/main/docs/README_legacy.md#12-local-development-environment)
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- [Yi-34B-Chat](https://platform.lingyiwanwu.com/) (Yi official beta)
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- Access is available through a whitelist. Welcome to apply (fill out a form in [English](https://cn.mikecrm.com/l91ODJf) or [Chinese](https://cn.mikecrm.com/gnEZjiQ)).
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### pip
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This tutorial guides you through every step of running Yi (Yi-34B-Chat) locally and then performing inference.
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#### Step 0: Prerequistes
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- This tutorial assumes you are running the **Yi-34B-Chat** with an **A800 (80G)** GPU.
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- For detailed deployment requirements to run Yi models, see [hardware requirements]( https://github.com/01-ai/Yi/blob/main/docs/deployment.md).
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- Make sure Python 3.10 or later version is installed.
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#### Step 1: Prepare your environment
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To set up the environment and install the required packages, execute the following command.
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pip install -r requirements.txt
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```
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#### Step 2: Download the Yi model
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You can download the weights and tokenizer of Yi models from the following sources:
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- [ModelScope](https://www.modelscope.cn/organization/01ai/)
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- [WiseModel](https://wisemodel.cn/organization/01.AI)
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#### Step 3: Perform inference
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You can perform inference with Yi chat or base models as below.
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##### Perform inference with Yi chat model
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1. Create a file named `quick_start.py` and copy the following content to it.
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Hello! How can I assist you today?
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```
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##### Perform inference with Yi base model
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The steps are similar to [Run Yi chat model](#run-yi-chat-model).
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</details>
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### Run Yi with llama.cpp
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If you have limited resources, you can try [llama.cpp](https://github.com/ggerganov/llama.cpp) or [ollama.cpp](https://ollama.ai/) (especially for Chinese users) to run Yi models in a few minutes locally.
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For a step-by-step tutorial,, see [Run Yi with llama.cpp](https://github.com/01-ai/Yi/edit/main/docs/yi_llama.cpp.md).
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### Web demo
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You can build a web UI demo for Yi **chat** models (note that Yi base models are not supported in this senario).
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[Step 1: Prepare your environment](#step-1-prepare-your-environment).
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[Step 2: Download the Yi model](#step-2-download-the-yi-model).
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Step 3. To start a web service locally, run the following command.
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```bash
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python demo/web_demo.py --checkpoint-path <your-model-path>
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```
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You can access the web UI by entering the address provided in the console into your browser.
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### Finetuning
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```bash
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via applications. All usage must adhere to the [Yi Series Models Community License Agreement 2.1](https://github.com/01-ai/Yi/blob/main/MODEL_LICENSE_AGREEMENT.txt).
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For free commercial use, you only need to send an email to [get official commercial permission](https://www.lingyiwanwu.com/yi-license).
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<div align="right"> [ <a href="#building-the-next-generation-of-open-source-and-bilingual-llms">Back to top ⬆️ </a> ] </div>
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