Merge branch '01-ai:main' into main

.github/workflows/build_docker_image.yml

@@ -74,18 +74,21 @@ jobs:
           echo "PRIMARY_TAG=$PRIMARY_TAG" >> "$GITHUB_OUTPUT"
           echo "PRIMARY_TAG_SHORT=$(echo $PRIMARY_TAG | cut -d ':' -f1)" >> "$GITHUB_OUTPUT"
       - name: Login to default container registry
+        if: matrix.runner == 'public'
         uses: docker/login-action@v2
         with:
           registry: ${{ secrets.DEFAULT_REGISTRY }}
           username: ${{ secrets.DEFAULT_REGISTRY_USER }}
           password: ${{ secrets.DEFAULT_REGISTRY_PASSWORD }}
       - name: Login to public container registry
+        if: matrix.runner == 'public'
         uses: docker/login-action@v2
         with:
           registry: ${{ secrets.PUBLIC_REGISTRY }}
           username: ${{ secrets.PUBLIC_REGISTRY_USER }}
           password: ${{ secrets.PUBLIC_REGISTRY_PASSWORD }}
       - name: Login to ghcr.io
+        if: matrix.runner == 'oversea'
         uses: docker/login-action@v2
         with:
           registry: ghcr.io
@@ -106,4 +109,4 @@ jobs:
           labels: ${{ steps.meta.outputs.labels }}
           cache-from: type=registry,ref=${{ steps.more-meta.outputs.PRIMARY_TAG_SHORT }}:buildcache
           cache-to: ${{ format('refs/heads/{0}', github.event.repository.default_branch) == github.ref && format('type=registry,image-manifest=true,ref={0}:buildcache,mode=max', steps.more-meta.outputs.PRIMARY_TAG_SHORT) || '' }}
-
+

README.md

@@ -2,8 +2,8 @@
 <p align="center">
 <img src="https://github.com/01-ai/Yi/raw/main/assets/img/Yi.svg?sanitize=true" width="200px">
 </p>
-<a href="https://github.com/01-ai/Yi/actions/workflows/ci.yml">
-  <img src="https://github.com/01-ai/Yi/actions/workflows/ci.yml/badge.svg">
+<a href="https://github.com/01-ai/Yi/actions/workflows/build_docker_image.yml">
+  <img src="https://github.com/01-ai/Yi/actions/workflows/build_docker_image.yml/badge.svg">
 </a>
 <a href="https://huggingface.co/01-ai">
   <img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-01--ai-blue">
@@ -114,6 +114,7 @@ The best approach to try the **Yi** series models is through Docker with GPUs. W
 provide the following docker images to help you get started.
 
 - `registry.lingyiwanwu.com/ci/01-ai/yi:latest`
+- `ghcr.io/01-ai/yi:latest`
 
 Note that the `latest` tag always points to the latest code in the `main`
 branch. To test a stable version, please replace it with a specific
@@ -252,6 +253,31 @@ python quantization/awq/eval_quantized_model.py \
 
 For more detailed explanation, please read the [doc](https://github.com/01-ai/Yi/tree/main/quantization/awq)
 
+## Ecosystem
+
+🤗 You are encouraged to create a PR and share your awesome work built on top of
+the Yi series models.
+
+- Serving
+  - [ScaleLLM](https://github.com/vectorch-ai/ScaleLLM#supported-models): Efficiently run Yi models locally.
+- Quantization
+  - [TheBloke/Yi-34B-GGUF](https://huggingface.co/TheBloke/Yi-34B-GGUF)
+  - [TheBloke/Yi-34B-GPTQ](https://huggingface.co/TheBloke/Yi-34B-GPTQ)
+- Finetuning
+  - [NousResearch/Nous-Capybara-34B](https://huggingface.co/NousResearch/Nous-Capybara-34B)
+
+## FAQ
+
+1. Will you release the chat version?
+
+  Yes, the chat version will be released around the end of November 2023.
+
+1. What dataset was this trained with?
+
+  The dataset we use contains Chinese & English only. We used approximately 3T
+  tokens. The detailed number and its construction will be described in the
+  upcoming technical report.
+
 ## Disclaimer
 
 We use data compliance checking algorithms during the training process, to