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README.md
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@@ -82,9 +82,11 @@ pipeline_tag: text-generation
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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](#quick-start---llamacpp)
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- [Web demo](#web-demo)
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- [Fine
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- [Quantization](#quantization)
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- [Deployment](#deployment)
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- [Learning hub](#learning-hub)
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- [📊 Chat model performance](#-chat-model-performance)
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- [🟢 Who can use Yi?](#-who-can-use-yi)
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- [🟢 Misc.](#-misc)
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-
- [
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- [📡 Disclaimer](#-disclaimer)
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- [🪪 License](#-license)
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@@ -122,7 +124,9 @@ pipeline_tag: text-generation
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- For Chinese language capability, the Yi series models landed in 2nd place (following GPT-4), surpassing other LLMs (such as Baidu ERNIE, Qwen, and Baichuan) on the [SuperCLUE](https://www.superclueai.com/) in Oct 2023.
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- 🙏 (Credits to LLaMA) Thanks to the Transformer and LLaMA open-source communities, as they reducing the efforts required to build from scratch and enabling the utilization of the same tools within the AI ecosystem.
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<details style="display: inline;"><summary> If you're interested in Yi's adoption of LLaMA architecture and license usage policy, see <span style="color: green;">Yi's relation with LLaMA.</span> ⬇️</summary> <ul> <br>
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> 💡 TL;DR
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>
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> The Yi series models adopt the same model architecture as LLaMA but are **NOT** derivatives of LLaMA.
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</ul>
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</details>
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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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@@ -207,67 +262,17 @@ Yi-6B-200K | • [🤗 Hugging Face](https://huggingface.co/01-ai/Yi-6B-200K)
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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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## 🎉 News
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<details>
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<summary>🎯 <b>2023/11/23</b>: The chat models are open to public.</summary>
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This release contains two chat models based on previously released base models, two 8-bit models quantized by GPTQ, and two 4-bit models quantized by AWQ.
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- `Yi-34B-Chat`
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- `Yi-34B-Chat-4bits`
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- `Yi-34B-Chat-8bits`
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- `Yi-6B-Chat`
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- `Yi-6B-Chat-4bits`
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- `Yi-6B-Chat-8bits`
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You can try some of them interactively at:
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- [Hugging Face](https://huggingface.co/spaces/01-ai/Yi-34B-Chat)
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- [Replicate](https://replicate.com/01-ai)
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</details>
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<details>
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<summary>🔔 <b>2023/11/23</b>: The Yi Series Models Community License Agreement is updated to v2.1.</summary>
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</details>
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<details>
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<summary>🔥 <b>2023/11/08</b>: Invited test of Yi-34B chat model.</summary>
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-
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Application form:
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- [English](https://cn.mikecrm.com/l91ODJf)
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- [Chinese](https://cn.mikecrm.com/gnEZjiQ)
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</details>
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<details>
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<summary>🎯 <b>2023/11/05</b>: The base model of <code>Yi-6B-200K</code> and <code>Yi-34B-200K</code>.</summary>
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This release contains two base models with the same parameter sizes as the previous
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release, except that the context window is extended to 200K.
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</details>
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<details>
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<summary>🎯 <b>2023/11/02</b>: The base model of <code>Yi-6B</code> and <code>Yi-34B</code>.</summary>
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The first public release contains two bilingual (English/Chinese) base models
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with the parameter sizes of 6B and 34B. Both of them are trained with 4K
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sequence length and can be extended to 32K during inference time.
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-
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</details>
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-
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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?
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- [Quick start](#quick-start)
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-
- [Choose your path](#choose-your-
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- [pip](#pip)
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- [llama.cpp](#quick-start---llamacpp)
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- [Web demo](#web-demo)
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-
- [Fine tune](#
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- [Quantization](#quantization)
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- [Deployment](#deployment)
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- [Learning hub](#learning-hub)
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@@ -289,7 +294,7 @@ 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](#quick-start---docker)
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- [conda-lock](
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- 🙋♀️ and you have **limited** resources (for example, a MacBook Pro), you can use [llama.cpp](#quick-start---llamacpp)
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@@ -449,7 +454,19 @@ ghcr.io/01-ai/yi:latest
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<p><strong>Note</strong> that the only difference is to set <code>--model <your-model-mount-path>'</code> instead of <code>model <your-model-path></code>.</p>
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</details>
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### Quick start - llama.cpp
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<details>
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![Quick start - web demo](https://github.com/01-ai/Yi/blob/main/assets/img/yi_34b_chat_web_demo.gif?raw=true)
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-
###
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```bash
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bash finetune/scripts/run_sft_Yi_6b.sh
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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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+
- [docker](#quick-start---docker)
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- [llama.cpp](#quick-start---llamacpp)
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- [conda-lock](#quick-start---conda-lock)
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- [Web demo](#web-demo)
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- [Fine-tuning](#fine-tuning)
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- [Quantization](#quantization)
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- [Deployment](#deployment)
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- [Learning hub](#learning-hub)
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- [📊 Chat model performance](#-chat-model-performance)
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- [🟢 Who can use Yi?](#-who-can-use-yi)
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- [🟢 Misc.](#-misc)
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- [Acknowledgements](#acknowledgments)
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- [📡 Disclaimer](#-disclaimer)
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- [🪪 License](#-license)
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- For Chinese language capability, the Yi series models landed in 2nd place (following GPT-4), surpassing other LLMs (such as Baidu ERNIE, Qwen, and Baichuan) on the [SuperCLUE](https://www.superclueai.com/) in Oct 2023.
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- 🙏 (Credits to LLaMA) Thanks to the Transformer and LLaMA open-source communities, as they reducing the efforts required to build from scratch and enabling the utilization of the same tools within the AI ecosystem.
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+
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<details style="display: inline;"><summary> If you're interested in Yi's adoption of LLaMA architecture and license usage policy, see <span style="color: green;">Yi's relation with LLaMA.</span> ⬇️</summary> <ul> <br>
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+
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> 💡 TL;DR
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>
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> The Yi series models adopt the same model architecture as LLaMA but are **NOT** derivatives of LLaMA.
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</ul>
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</details>
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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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## 🎉 News
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<details open>
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<summary>🎯 <b>2024/01/23</b>: The Yi-VL models, <code><a href="https://huggingface.co/01-ai/Yi-VL-34B">Yi-VL-34B</a></code> and <code><a href="https://huggingface.co/01-ai/Yi-VL-6B">Yi-VL-6B</a></code>, are open-sourced and available to the public.</summary>
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<br>
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<code><a href="https://huggingface.co/01-ai/Yi-VL-34B">Yi-VL-34B</a></code> has ranked <strong>first</strong> among all existing open-source models in the latest benchmarks, including <a href="https://arxiv.org/abs/2311.16502">MMMU</a> and <a href="https://arxiv.org/abs/2401.11944">CMMMU</a> (based on data available up to January 2024).</li>
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</details>
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<details>
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<summary>🎯 <b>2023/11/23</b>: <a href="#chat-models">Chat models</a> are open-sourced and available to the public.</summary>
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<br>This release contains two chat models based on previously released base models, two 8-bit models quantized by GPTQ, and two 4-bit models quantized by AWQ.
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+
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- `Yi-34B-Chat`
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- `Yi-34B-Chat-4bits`
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- `Yi-34B-Chat-8bits`
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- `Yi-6B-Chat`
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- `Yi-6B-Chat-4bits`
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- `Yi-6B-Chat-8bits`
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You can try some of them interactively at:
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- [Hugging Face](https://huggingface.co/spaces/01-ai/Yi-34B-Chat)
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- [Replicate](https://replicate.com/01-ai)
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</details>
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<details>
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<summary>🔔 <b>2023/11/23</b>: The Yi Series Models Community License Agreement is updated to <a href="https://github.com/01-ai/Yi/blob/main/MODEL_LICENSE_AGREEMENT.txt">v2.1</a>.</summary>
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</details>
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<details>
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<summary>🔥 <b>2023/11/08</b>: Invited test of Yi-34B chat model.</summary>
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<br>Application form:
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- [English](https://cn.mikecrm.com/l91ODJf)
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- [Chinese](https://cn.mikecrm.com/gnEZjiQ)
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</details>
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<details>
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<summary>🎯 <b>2023/11/05</b>: <a href="#base-models">The base models, </a><code>Yi-6B-200K</code> and <code>Yi-34B-200K</code>, are open-sourced and available to the public.</summary>
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<br>This release contains two base models with the same parameter sizes as the previous
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release, except that the context window is extended to 200K.
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</details>
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+
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<details>
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<summary>🎯 <b>2023/11/02</b>: <a href="#base-models">The base models, </a><code>Yi-6B</code> and <code>Yi-34B</code>, are open-sourced and available to the public.</summary>
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<br>The first public release contains two bilingual (English/Chinese) base models
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with the parameter sizes of 6B and 34B. Both of them are trained with 4K
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sequence length and can be extended to 32K during inference time.
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+
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</details>
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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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<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?
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- [Quick start](#quick-start)
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+
- [Choose your path](#choose-your-path)
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- [pip](#pip)
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+
- [docker](#quick-start---docker)
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+
- [conda-lock](#quick-start---conda-lock)
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- [llama.cpp](#quick-start---llamacpp)
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- [Web demo](#web-demo)
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- [Fine tune](#finetuning)
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- [Quantization](#quantization)
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- [Deployment](#deployment)
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- [Learning hub](#learning-hub)
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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](#quick-start---docker)
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+
- [conda-lock](#quick-start---conda-lock)
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- 🙋♀️ and you have **limited** resources (for example, a MacBook Pro), you can use [llama.cpp](#quick-start---llamacpp)
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<p><strong>Note</strong> that the only difference is to set <code>--model <your-model-mount-path>'</code> instead of <code>model <your-model-path></code>.</p>
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</details>
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### Quick start - conda-lock
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<details>
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<summary>You can use <code><a href="https://github.com/conda/conda-lock">conda-lock</a></code> to generate fully reproducible lock files for conda environments. ⬇️</summary>
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<br>
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You can refer to <a href="https://github.com/01-ai/Yi/blob/ebba23451d780f35e74a780987ad377553134f68/conda-lock.yml">conda-lock.yml</a> for the exact versions of the dependencies. Additionally, you can utilize <code><a href="https://mamba.readthedocs.io/en/latest/user_guide/micromamba.html">micromamba</a></code> for installing these dependencies.
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<br>
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To install the dependencies, follow these steps:
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1. Install micromamba by following the instructions available <a href="https://mamba.readthedocs.io/en/latest/installation/micromamba-installation.html">here</a>.
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2. Execute <code>micromamba install -y -n yi -f conda-lock.yml</code> to create a conda environment named <code>yi</code> and install the necessary dependencies.
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</details>
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### Quick start - llama.cpp
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<details>
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![Quick start - web demo](https://github.com/01-ai/Yi/blob/main/assets/img/yi_34b_chat_web_demo.gif?raw=true)
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### Fine-tuning
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```bash
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bash finetune/scripts/run_sft_Yi_6b.sh
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