Instructions to use sail/Sailor-4B-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sail/Sailor-4B-Chat with Transformers:

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

pipe = pipeline("text-generation", model="sail/Sailor-4B-Chat")
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("sail/Sailor-4B-Chat")
model = AutoModelForCausalLM.from_pretrained("sail/Sailor-4B-Chat", 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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use sail/Sailor-4B-Chat with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sail/Sailor-4B-Chat"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sail/Sailor-4B-Chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/sail/Sailor-4B-Chat

SGLang

How to use sail/Sailor-4B-Chat 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 "sail/Sailor-4B-Chat" \
    --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": "sail/Sailor-4B-Chat",
		"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 "sail/Sailor-4B-Chat" \
        --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": "sail/Sailor-4B-Chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use sail/Sailor-4B-Chat with Docker Model Runner:
```
docker model run hf.co/sail/Sailor-4B-Chat
```

SivilTaram commited on Mar 5, 2024

Commit

462e044

verified ·

1 Parent(s): ca090f1

Update README.md

Browse files

Add examples in different languages

Files changed (1) hide show

README.md +13 -4

README.md CHANGED Viewed

@@ -8,10 +8,6 @@ language:
 - ms
 - lo
 datasets:
-- cerebras/SlimPajama-627B
-- Skywork/SkyPile-150B
-- allenai/MADLAD-400
-- cc100
 - CohereForAI/aya_dataset
 - CohereForAI/aya_collection
 - Open-Orca/OpenOrca
@@ -22,6 +18,19 @@ tags:
 - sft
 - chat
 - instruction
 license: apache-2.0
 base_model: sail/Sailor-4B
 ---

 - ms
 - lo
 datasets:
 - CohereForAI/aya_dataset
 - CohereForAI/aya_collection
 - Open-Orca/OpenOrca
 - sft
 - chat
 - instruction
+widget:
+- text: "如何制作烤鱼？"
+  example_title: "Chinese"
+- text: "How to bake fish?"
+  example_title: "English"
+- text: "Bagaimana cara memanggang ikan?"
+  example_title: "Malay"
+- text: "วิธีย่างปลา?"
+  example_title: "Thai"
+- text: "Bagaimana membuat bakaran ikan?"
+  example_title: "Indonesian"
+- text: "Làm thế nào để nướng cá?"
+  example_title: "Vietnamese"
 license: apache-2.0
 base_model: sail/Sailor-4B
 ---