Instructions to use DAMO-NLP-MT/polylm-multialpaca-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DAMO-NLP-MT/polylm-multialpaca-13b with Transformers:

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

pipe = pipeline("text-generation", model="DAMO-NLP-MT/polylm-multialpaca-13b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DAMO-NLP-MT/polylm-multialpaca-13b")
model = AutoModelForCausalLM.from_pretrained("DAMO-NLP-MT/polylm-multialpaca-13b")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use DAMO-NLP-MT/polylm-multialpaca-13b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DAMO-NLP-MT/polylm-multialpaca-13b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DAMO-NLP-MT/polylm-multialpaca-13b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/DAMO-NLP-MT/polylm-multialpaca-13b

SGLang

How to use DAMO-NLP-MT/polylm-multialpaca-13b 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 "DAMO-NLP-MT/polylm-multialpaca-13b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DAMO-NLP-MT/polylm-multialpaca-13b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "DAMO-NLP-MT/polylm-multialpaca-13b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DAMO-NLP-MT/polylm-multialpaca-13b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use DAMO-NLP-MT/polylm-multialpaca-13b with Docker Model Runner:
```
docker model run hf.co/DAMO-NLP-MT/polylm-multialpaca-13b
```

Prompt format?

by passaglia - opened Jul 18, 2023

Discussion

passaglia

Jul 18, 2023

What is the exact prompt format for this model? The paper does not explicitly say.

Is it the same as alpaca:

"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Input:\n{input}\n\n### Response:\n"

pemywei

Machine Translation Team at Alibaba DAMO Academy org Jul 18, 2023

There is no predefined prompt, simply pass the query to the model, but add two \n at the end of the prompt, e.g., https://huggingface.co/DAMO-NLP-MT/polylm-multialpaca-13b/blob/main/polylm_cli_demo.py#L73

passaglia

Jul 18, 2023

Great, thank you.

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