[ChatQnA] Update README for ModelScope (#770)

Signed-off-by: letonghan <letong.han@intel.com>
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Letong Han
2024-09-10 13:50:36 +08:00
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commit aebc23f5ae
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@@ -139,6 +139,8 @@ By default, the embedding, reranking and LLM models are set to a default value a
Change the `xxx_MODEL_ID` in `docker/xxx/set_env.sh` for your needs.
For customers with proxy issues, the models from [ModelScope](https://www.modelscope.cn/models) are also supported in ChatQnA. Refer to [this readme](docker/xeon/README.md) for details.
### Setup Environment Variable
To set up environment variables for deploying ChatQnA services, follow these steps:

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@@ -188,6 +188,31 @@ By default, the embedding, reranking and LLM models are set to a default value a
Change the `xxx_MODEL_ID` below for your needs.
For customers with proxy issues, the models from [ModelScope](https://www.modelscope.cn/models) are also supported in ChatQnA with TGI serving. ModelScope models are supported in two ways for TGI:
1. Online
```bash
export HF_TOKEN=${your_hf_token}
export HF_ENDPOINT="https://hf-mirror.com"
model_name="Intel/neural-chat-7b-v3-3"
docker run -p 8008:80 -v ./data:/data --name tgi-service -e HF_ENDPOINT=$HF_ENDPOINT -e http_proxy=$http_proxy -e https_proxy=$https_proxy --shm-size 1g ghcr.io/huggingface/text-generation-inference:2.1.0 --model-id $model_name
```
2. Offline
- Search your model name in ModelScope. For example, check [this page](https://www.modelscope.cn/models/ai-modelscope/neural-chat-7b-v3-1/files) for model `neural-chat-7b-v3-1`.
- Click on `Download this model` button, and choose one way to download the model to your local path `/path/to/model`.
- Run the following command to start TGI service.
```bash
export HF_TOKEN=${your_hf_token}
export model_path="/path/to/model"
docker run -p 8008:80 -v $model_path:/data --name tgi_service --shm-size 1g ghcr.io/huggingface/text-generation-inference:2.1.0 --model-id /data
```
### Setup Environment Variables
Since the `compose.yaml` will consume some environment variables, you need to setup them in advance as below.

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@@ -188,6 +188,31 @@ By default, the embedding, reranking and LLM models are set to a default value a
Change the `xxx_MODEL_ID` below for your needs.
For customers with proxy issues, the models from [ModelScope](https://www.modelscope.cn/models) are also supported in ChatQnA with TGI serving. ModelScope models are supported in two ways for TGI:
1. Online
```bash
export HF_TOKEN=${your_hf_token}
export HF_ENDPOINT="https://hf-mirror.com"
model_name="Intel/neural-chat-7b-v3-3"
docker run -p 8008:80 -v ./data:/data --name tgi-service -e HF_ENDPOINT=$HF_ENDPOINT -e http_proxy=$http_proxy -e https_proxy=$https_proxy --shm-size 1g ghcr.io/huggingface/text-generation-inference:2.1.0 --model-id $model_name
```
2. Offline
- Search your model name in ModelScope. For example, check [this page](https://www.modelscope.cn/models/ai-modelscope/neural-chat-7b-v3-1/files) for model `neural-chat-7b-v3-1`.
- Click on `Download this model` button, and choose one way to download the model to your local path `/path/to/model`.
- Run the following command to start TGI service.
```bash
export HF_TOKEN=${your_hf_token}
export model_path="/path/to/model"
docker run -p 8008:80 -v $model_path:/data --name tgi_service --shm-size 1g ghcr.io/huggingface/text-generation-inference:2.1.0 --model-id /data
```
### Setup Environment Variables
Since the `compose.yaml` will consume some environment variables, you need to setup them in advance as below.