Instructions to use LiquidAI/LFM2-350M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LiquidAI/LFM2-350M with Transformers:

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

pipe = pipeline("text-generation", model="LiquidAI/LFM2-350M")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("LiquidAI/LFM2-350M")
model = AutoModelForCausalLM.from_pretrained("LiquidAI/LFM2-350M")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use LiquidAI/LFM2-350M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LiquidAI/LFM2-350M"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LiquidAI/LFM2-350M",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/LiquidAI/LFM2-350M

SGLang

How to use LiquidAI/LFM2-350M 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 "LiquidAI/LFM2-350M" \
    --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": "LiquidAI/LFM2-350M",
		"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 "LiquidAI/LFM2-350M" \
        --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": "LiquidAI/LFM2-350M",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use LiquidAI/LFM2-350M with Docker Model Runner:
```
docker model run hf.co/LiquidAI/LFM2-350M
```

Error out in VLLM

by rmadupu - opened Jul 20, 2025

Discussion

rmadupu

Jul 20, 2025

(vllm) rakesh@instance-20250720-112712:~$ sudo vllm serve "LiquidAI/LFM2-350M"
Traceback (most recent call last):
  File "/usr/local/bin/vllm", line 5, in <module>
    from vllm.entrypoints.cli.main import main
  File "/usr/local/lib/python3.9/dist-packages/vllm/entrypoints/cli/__init__.py", line 3, in <module>
    from vllm.entrypoints.cli.benchmark.latency import BenchmarkLatencySubcommand
  File "/usr/local/lib/python3.9/dist-packages/vllm/entrypoints/cli/benchmark/latency.py", line 5, in <module>
    from vllm.benchmarks.latency import add_cli_args, main
  File "/usr/local/lib/python3.9/dist-packages/vllm/benchmarks/latency.py", line 16, in <module>
    from vllm import LLM, SamplingParams
  File "<frozen importlib._bootstrap>", line 1055, in _handle_fromlist
  File "/usr/local/lib/python3.9/dist-packages/vllm/__init__.py", line 64, in __getattr__
    module = import_module(module_name, __package__)
  File "/usr/lib/python3.9/importlib/__init__.py", line 127, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "/usr/local/lib/python3.9/dist-packages/vllm/entrypoints/llm.py", line 20, in <module>
    from vllm.config import (CompilationConfig, ModelDType, TokenizerMode,
  File "/usr/local/lib/python3.9/dist-packages/vllm/config.py", line 36, in <module>
    from vllm.platforms import current_platform
  File "<frozen importlib._bootstrap>", line 1055, in _handle_fromlist
  File "/usr/local/lib/python3.9/dist-packages/vllm/platforms/__init__.py", line 275, in __getattr__
    platform_cls_qualname = resolve_current_platform_cls_qualname()
  File "/usr/local/lib/python3.9/dist-packages/vllm/platforms/__init__.py", line 210, in resolve_current_platform_cls_qualname
    platform_plugins = load_plugins_by_group('vllm.platform_plugins')
  File "/usr/local/lib/python3.9/dist-packages/vllm/plugins/__init__.py", line 29, in load_plugins_by_group
    discovered_plugins = entry_points(group=group)
TypeError: entry_points() got an unexpected keyword argument 'group'
(vllm) rakesh@instance-20250720-112712:~$

Do I need to have a higher python version ?

alvarobartt

Jul 21, 2025

In case this helps https://github.com/vllm-project/vllm/issues/20776

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment