mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2026-04-23 00:17:25 +08:00
[XPU] Update doc and add scripts for downloading dependencies (#2845)
* [XPU] update xvllm download * update supported models * fix xpu model runner in huge memory with small model * update doc
This commit is contained in:
@@ -0,0 +1,92 @@
|
||||
## Supported Models
|
||||
|Model Name|Context Length|Quantization|XPUs Required|Deployment Commands|
|
||||
|-|-|-|-|-|
|
||||
|ERNIE-4.5-300B-A47B|32K|WINT8|8|export XPU_VISIBLE_DEVICES="0,1,2,3,4,5,6,7"<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-300B-A47B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 8 \ <br> --max-model-len 32768 \ <br> --max-num-seqs 64 \ <br> --quantization "wint8" \ <br> --gpu-memory-utilization 0.9|
|
||||
|ERNIE-4.5-300B-A47B|32K|WINT4|4 (recommend)|export XPU_VISIBLE_DEVICES="0,1,2,3" or "4,5,6,7"<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-300B-A47B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 4 \ <br> --max-model-len 32768 \ <br> --max-num-seqs 64 \ <br> --quantization "wint4" \ <br> --gpu-memory-utilization 0.9|
|
||||
|ERNIE-4.5-300B-A47B|32K|WINT4|8|export XPU_VISIBLE_DEVICES="0,1,2,3,4,5,6,7"<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-300B-A47B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 8 \ <br> --max-model-len 32768 \ <br> --max-num-seqs 64 \ <br> --quantization "wint4" \ <br> --gpu-memory-utilization 0.9|
|
||||
|ERNIE-4.5-300B-A47B|128K|WINT4|8 (recommend)|export XPU_VISIBLE_DEVICES="0,1,2,3,4,5,6,7"<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-300B-A47B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 8 \ <br> --max-model-len 131072 \ <br> --max-num-seqs 64 \ <br> --quantization "wint4" \ <br> --gpu-memory-utilization 0.9|
|
||||
|ERNIE-4.5-21B-A3B|32K|BF16|1|export XPU_VISIBLE_DEVICES="0" # Specify any card<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-21B-A3B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 1 \ <br> --max-model-len 32768 \ <br> --max-num-seqs 128 \ <br> --gpu-memory-utilization 0.9|
|
||||
|ERNIE-4.5-21B-A3B|32K|WINT8|1|export XPU_VISIBLE_DEVICES="0" # Specify any card<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-21B-A3B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 1 \ <br> --max-model-len 32768 \ <br> --max-num-seqs 128 \ <br> --quantization "wint8" \ <br> --gpu-memory-utilization 0.9|
|
||||
|ERNIE-4.5-21B-A3B|32K|WINT4|1|export XPU_VISIBLE_DEVICES="0" # Specify any card<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-21B-A3B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 1 \ <br> --max-model-len 32768 \ <br> --max-num-seqs 128 \ <br> --quantization "wint4" \ <br> --gpu-memory-utilization 0.9|
|
||||
|ERNIE-4.5-21B-A3B|128K|BF16|1|export XPU_VISIBLE_DEVICES="0" # Specify any card<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-21B-A3B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 1 \ <br> --max-model-len 131072 \ <br> --max-num-seqs 128 \ <br> --gpu-memory-utilization 0.9|
|
||||
|ERNIE-4.5-21B-A3B|128K|WINT8|1|export XPU_VISIBLE_DEVICES="0" # Specify any card<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-21B-A3B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 1 \ <br> --max-model-len 131072 \ <br> --max-num-seqs 128 \ <br> --quantization "wint8" \ <br> --gpu-memory-utilization 0.9|
|
||||
|ERNIE-4.5-21B-A3B|128K|WINT4|1|export XPU_VISIBLE_DEVICES="0" # Specify any card<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-21B-A3B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 1 \ <br> --max-model-len 131072 \ <br> --max-num-seqs 128 \ <br> --quantization "wint4" \ <br> --gpu-memory-utilization 0.9|
|
||||
|ERNIE-4.5-0.3B|32K|BF16|1|export XPU_VISIBLE_DEVICES="0" # Specify any card<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-0.3B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 1 \ <br> --max-model-len 32768 \ <br> --max-num-seqs 128 \ <br> --gpu-memory-utilization 0.9|
|
||||
|ERNIE-4.5-0.3B|32K|WINT8|1|export XPU_VISIBLE_DEVICES="x" # Specify any card<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-0.3B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 1 \ <br> --max-model-len 32768 \ <br> --max-num-seqs 128 \ <br> --quantization "wint8" \ <br> --gpu-memory-utilization 0.9|
|
||||
|ERNIE-4.5-0.3B|128K|BF16|1|export XPU_VISIBLE_DEVICES="0" # Specify any card<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-0.3B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 1 \ <br> --max-model-len 131072 \ <br> --max-num-seqs 128 \ <br> --gpu-memory-utilization 0.9|
|
||||
|ERNIE-4.5-0.3B|128K|WINT8|1|export XPU_VISIBLE_DEVICES="0" # Specify any card<br>python -m fastdeploy.entrypoints.openai.api_server \ <br> --model PaddlePaddle/ERNIE-4.5-0.3B-Paddle \ <br> --port 8188 \ <br> --tensor-parallel-size 1 \ <br> --max-model-len 131072 \ <br> --max-num-seqs 128 \ <br> --quantization "wint8" \ <br> --gpu-memory-utilization 0.9|
|
||||
|
||||
## Quick start
|
||||
|
||||
### Online serving (OpenAI API-Compatible server)
|
||||
|
||||
Deploy an OpenAI API-compatible server using FastDeploy with the following commands:
|
||||
|
||||
#### Start service
|
||||
|
||||
**Deploy the ERNIE-4.5-300B-A47B-Paddle model with WINT4 precision and 32K context length on 4 XPUs**
|
||||
|
||||
```bash
|
||||
export XPU_VISIBLE_DEVICES="0,1,2,3" # Specify which cards to be used
|
||||
python -m fastdeploy.entrypoints.openai.api_server \
|
||||
--model baidu/ERNIE-4.5-300B-A47B-Paddle \
|
||||
--port 8188 \
|
||||
--tensor-parallel-size 4 \
|
||||
--max-model-len 32768 \
|
||||
--max-num-seqs 64 \
|
||||
--quantization "wint4" \
|
||||
--gpu-memory-utilization 0.9
|
||||
```
|
||||
|
||||
**Note:** When deploying on 4 XPUs, only two configurations are supported which constrained by hardware limitations such as interconnect capabilities.
|
||||
`export XPU_VISIBLE_DEVICES="0,1,2,3"`
|
||||
or
|
||||
`export XPU_VISIBLE_DEVICES="4,5,6,7"`
|
||||
|
||||
Refer to [Parameters](../../parameters.md) for more options.
|
||||
|
||||
All supported models can be found in the *Supported Models* section above.
|
||||
|
||||
#### Send requests
|
||||
|
||||
Send requests using either curl or Python
|
||||
|
||||
```bash
|
||||
curl -X POST "http://0.0.0.0:8188/v1/chat/completions" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"messages": [
|
||||
{"role": "user", "content": "Where is the capital of China?"}
|
||||
]
|
||||
}'
|
||||
```
|
||||
|
||||
```python
|
||||
import openai
|
||||
host = "0.0.0.0"
|
||||
port = "8188"
|
||||
client = openai.Client(base_url=f"http://{host}:{port}/v1", api_key="null")
|
||||
|
||||
response = client.completions.create(
|
||||
model="null",
|
||||
prompt="Where is the capital of China?",
|
||||
stream=True,
|
||||
)
|
||||
for chunk in response:
|
||||
print(chunk.choices[0].text, end='')
|
||||
print('\n')
|
||||
|
||||
response = client.chat.completions.create(
|
||||
model="null",
|
||||
messages=[
|
||||
{"role": "user", "content": "Where is the capital of China?"},
|
||||
],
|
||||
stream=True,
|
||||
)
|
||||
for chunk in response:
|
||||
if chunk.choices[0].delta:
|
||||
print(chunk.choices[0].delta.content, end='')
|
||||
print('\n')
|
||||
```
|
||||
|
||||
For detailed OpenAI protocol specifications, see [OpenAI Chat Compeltion API](https://platform.openai.com/docs/api-reference/chat/create). Differences from the standard OpenAI protocol are documented in [OpenAI Protocol-Compatible API Server](../../online_serving/README.md).
|
||||
Reference in New Issue
Block a user