Instructions to use zelapi/lilo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zelapi/lilo with Transformers:

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

pipe = pipeline("text-generation", model="zelapi/lilo", 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("zelapi/lilo", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("zelapi/lilo", 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 zelapi/lilo with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/zelapi/lilo

SGLang

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

Docker Model Runner
How to use zelapi/lilo with Docker Model Runner:
```
docker model run hf.co/zelapi/lilo
```

lilo

File size: 1,232 Bytes

36a88b2

{%- if not add_generation_prompt is defined -%}
	{%- set add_generation_prompt = false -%}
{%- endif -%}
{%- set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt="", is_first_sp=true) -%}
{%- for message in messages -%}
	{%- if message["role"] == "system" -%}
		{%- if ns.is_first_sp -%}
			{%- set ns.system_prompt = ns.system_prompt + message["content"] -%}
			{%- set ns.is_first_sp = false -%}
		{%- else -%}
			{%- set ns.system_prompt = ns.system_prompt + "\n\n" + message["content"] -%}
		{%- endif -%}
	{%- endif -%}
{%- endfor -%}
{{- bos_token -}}
{{- ns.system_prompt -}}
{%- for message in messages -%}
	{%- if message["role"] == "user" -%}
		{%- set ns.is_tool = false -%}
		{{- "<｜User｜>" + message["content"] -}}
	{%- endif -%}
	{%- if message["role"] == "assistant" and message["content"] is not none -%}
		{%- if ns.is_tool -%}
			{{- "<｜tool▁outputs▁end｜>" + message["content"] + "<｜end▁of▁sentence｜>" -}}
			{%- set ns.is_tool = false -%}
		{%- else -%}
			{{- "<｜Assistant｜>" + message["content"] + "<｜end▁of▁sentence｜>" -}}
		{%- endif -%}
	{%- endif -%}
{%- endfor -%}
{%- if add_generation_prompt -%}
	{{- "<｜Assistant｜>" -}}
{%- endif -%}