Instructions to use rostlabs/rost-1b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use rostlabs/rost-1b-instruct with Transformers:

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

pipe = pipeline("text-generation", model="rostlabs/rost-1b-instruct", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("rostlabs/rost-1b-instruct", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use rostlabs/rost-1b-instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "rostlabs/rost-1b-instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "rostlabs/rost-1b-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/rostlabs/rost-1b-instruct

SGLang

How to use rostlabs/rost-1b-instruct 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 "rostlabs/rost-1b-instruct" \
    --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": "rostlabs/rost-1b-instruct",
		"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 "rostlabs/rost-1b-instruct" \
        --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": "rostlabs/rost-1b-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use rostlabs/rost-1b-instruct with Docker Model Runner:
```
docker model run hf.co/rostlabs/rost-1b-instruct
```

stefaniancu commited on 5 days ago

Commit

8ac458f

verified ·

1 Parent(s): 19e82b3

Ship the decoding settings, and a stop condition

Browse files

Files changed (1) hide show

generation_config.json +14 -0

generation_config.json ADDED Viewed

	@@ -0,0 +1,14 @@

+{
+  "_from_model_config": false,
+  "bos_token_id": 32759,
+  "eos_token_id": [
+    32763,
+    32759
+  ],
+  "pad_token_id": 32763,
+  "do_sample": true,
+  "temperature": 0.6,
+  "top_k": 50,
+  "repetition_penalty": 1.1,
+  "max_new_tokens": 512
+}