Instructions to use BAAI/Aquila2-34B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use BAAI/Aquila2-34B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="BAAI/Aquila2-34B", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("BAAI/Aquila2-34B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use BAAI/Aquila2-34B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "BAAI/Aquila2-34B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BAAI/Aquila2-34B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/BAAI/Aquila2-34B

SGLang

How to use BAAI/Aquila2-34B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "BAAI/Aquila2-34B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BAAI/Aquila2-34B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "BAAI/Aquila2-34B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BAAI/Aquila2-34B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use BAAI/Aquila2-34B with Docker Model Runner:
```
docker model run hf.co/BAAI/Aquila2-34B
```

ldwang commited on Jul 13

Commit

d0ff5a6

verified ·

1 Parent(s): 131a9b7

Update README.md

Browse files

Files changed (1) hide show

README.md +7 -1

README.md CHANGED Viewed

@@ -94,4 +94,10 @@ Feel free to cite the repo if you think Aquila2 is useful.
       primaryClass={cs.CL},
       url={https://arxiv.org/abs/2408.07410},
 }
-```

       primaryClass={cs.CL},
       url={https://arxiv.org/abs/2408.07410},
 }
+```
+# Acknowledgements
+This work is supported by the National Science and Technology Major Project (No. 2022ZD0116300).
+本项目受新一代人工智能国家科技重大专项（No. 2022ZD0116300）支持。