Instructions to use Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound with Transformers:

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

pipe = pipeline("text-generation", model="Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import LongcatCausalLM
model = LongcatCausalLM.from_pretrained("Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound

SGLang

How to use Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound 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 "Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound" \
    --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": "Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound",
		"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 "Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound" \
        --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": "Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound with Docker Model Runner:
```
docker model run hf.co/Intel/LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound
```

LongCat-Flash-Lite-Sparse-MXFP4-CT-AutoRound / quantization_config.json

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	{
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	"model.layers.13.mlps.1.up_proj",
	"model.layers.13.self_attn.1.kv_a_proj_with_mqa",
	"model.layers.13.self_attn.1.o_proj",
	"model.layers.2.mlps.0.up_proj",
	"model.layers.3.mlps.1.up_proj",
	"model.layers.4.mlps.0.gate_proj",
	"model.layers.5.mlps.0.up_proj",
	"model.layers.7.self_attn.1.q_b_proj",
	"model.layers.8.mlps.0.down_proj",
	"model.layers.8.self_attn.0.q_a_proj",
	"model.layers.9.mlps.1.down_proj",
	"model.layers.9.self_attn.0.indexer.wk",
	"model.oe_embed_proj7"
	],
	"provider": "auto-round"
	}