Instructions to use SeaLLMs/SeaLLM-7B-v2.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SeaLLMs/SeaLLM-7B-v2.5 with Transformers:

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

pipe = pipeline("text-generation", model="SeaLLMs/SeaLLM-7B-v2.5")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("SeaLLMs/SeaLLM-7B-v2.5")
model = AutoModelForMultimodalLM.from_pretrained("SeaLLMs/SeaLLM-7B-v2.5")
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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use SeaLLMs/SeaLLM-7B-v2.5 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SeaLLMs/SeaLLM-7B-v2.5"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SeaLLMs/SeaLLM-7B-v2.5",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/SeaLLMs/SeaLLM-7B-v2.5

SGLang

How to use SeaLLMs/SeaLLM-7B-v2.5 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 "SeaLLMs/SeaLLM-7B-v2.5" \
    --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": "SeaLLMs/SeaLLM-7B-v2.5",
		"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 "SeaLLMs/SeaLLM-7B-v2.5" \
        --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": "SeaLLMs/SeaLLM-7B-v2.5",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use SeaLLMs/SeaLLM-7B-v2.5 with Docker Model Runner:
```
docker model run hf.co/SeaLLMs/SeaLLM-7B-v2.5
```

About Sea LLM technical cooperation

by onlyone156 - opened Jun 26, 2024

Discussion

onlyone156

Jun 26, 2024

Hello, I am a software engineer from China and a company that has deep cooperation with Southeast Asia（云南广电集团）. We are currently incubating a big model service for Southeast Asian people. We aim to use open source big models to serve the local education and tourism industries. Our company sincerely wants to invite your technical team to discuss some related cooperation matters.

Jianyu

SeaLLMs - Language Models for Southeast Asian Languages org Jun 27, 2024

Hi, thanks for your interests.

If you are interested in further discussions, please contact Dr. Bing: l.bing@alibaba-inc.com

And please also cc to Wenxuan: saike.zwx@alibaba-inc.com

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