Instructions to use aisingapore/SEA-LION-v1-7B-IT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use aisingapore/SEA-LION-v1-7B-IT with Transformers:

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

pipe = pipeline("text-generation", model="aisingapore/SEA-LION-v1-7B-IT", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("aisingapore/SEA-LION-v1-7B-IT", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("aisingapore/SEA-LION-v1-7B-IT", trust_remote_code=True, device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use aisingapore/SEA-LION-v1-7B-IT with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "aisingapore/SEA-LION-v1-7B-IT"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "aisingapore/SEA-LION-v1-7B-IT",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/aisingapore/SEA-LION-v1-7B-IT

SGLang

How to use aisingapore/SEA-LION-v1-7B-IT 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 "aisingapore/SEA-LION-v1-7B-IT" \
    --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": "aisingapore/SEA-LION-v1-7B-IT",
		"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 "aisingapore/SEA-LION-v1-7B-IT" \
        --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": "aisingapore/SEA-LION-v1-7B-IT",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use aisingapore/SEA-LION-v1-7B-IT with Docker Model Runner:
```
docker model run hf.co/aisingapore/SEA-LION-v1-7B-IT
```

Unclear instructions

by agoudarzi - opened Apr 9, 2024

Discussion

agoudarzi

Apr 9, 2024

I deployed this model on the Vertex AI but I get Incomplete generation error:


prompt = """
### USER:\n Apa sentimen dari kalimat berikut ini?
Kalimat: Buku ini sangat membosankan.
Jawaban:  \n\n### RESPONSE:\n
"""

messages = { "instances" : [ { "inputs" : prompt}], 
"parameters" : { "max_new_tokens" : 100} }

headers = {
    "Content-Type": "application/json",
    "Authorization" : f"Bearer {token}"
}

print( headers)
url = f"https://us-central1-aiplatform.googleapis.com/v1/projects/{PROJECT_ID}/locations/us-central1/endpoints/{ENDPOINT_ID}:predict"
print(url)
t0 = time.time()
results = requests.post(url, json=messages, headers=headers)
t1 = time.time()

print(results.content)

print(t1-t0)

RaymondAISG

AI Singapore org Apr 11, 2024

Dear @agoudarzi ,

Thank you for your interests in SEA-LION.
Could you elaborate more on the error you have encountered by sharing any error messages you have received when running this code?

Or do you meant the generated text was incomplete? If yes, could you kindly increase the value for max_new_tokens to a higher value (e.g. 1000) and see if the model is able to completely answer your query?

Thank you
Raymond

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