Instructions to use amd/Kimi-K2.5-W4A8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use amd/Kimi-K2.5-W4A8 with Transformers:

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

pipe = pipeline("image-text-to-text", model="amd/Kimi-K2.5-W4A8", trust_remote_code=True)
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("amd/Kimi-K2.5-W4A8", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use amd/Kimi-K2.5-W4A8 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "amd/Kimi-K2.5-W4A8"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "amd/Kimi-K2.5-W4A8",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/amd/Kimi-K2.5-W4A8

SGLang

How to use amd/Kimi-K2.5-W4A8 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 "amd/Kimi-K2.5-W4A8" \
    --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": "amd/Kimi-K2.5-W4A8",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "amd/Kimi-K2.5-W4A8" \
        --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": "amd/Kimi-K2.5-W4A8",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use amd/Kimi-K2.5-W4A8 with Docker Model Runner:
```
docker model run hf.co/amd/Kimi-K2.5-W4A8
```

vLLM v0.19.0 Serving error

by trustyourinstinct - opened Apr 14

Discussion

trustyourinstinct

Apr 14

I am trying to run this quantized model on an MI300 host with the latest stable of vLLM (v0.19.0) but seem to encounter an issue with the quant config stage:

(APIServer pid=1) Traceback (most recent call last):
(APIServer pid=1)   File "/usr/local/bin/vllm", line 10, in <module>
(APIServer pid=1)     sys.exit(main())
(APIServer pid=1)              ^^^^^^
(APIServer pid=1)   File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/cli/main.py", line 75, in main
(APIServer pid=1)     args.dispatch_function(args)
(APIServer pid=1)   File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/cli/serve.py", line 122, in cmd
(APIServer pid=1)     uvloop.run(run_server(args))
(APIServer pid=1)   File "/usr/local/lib/python3.12/dist-packages/uvloop/__init__.py", line 96, in run
(APIServer pid=1)     return __asyncio.run(
(APIServer pid=1)            ^^^^^^^^^^^^^^
(APIServer pid=1)   File "/usr/lib/python3.12/asyncio/runners.py", line 195, in run
(APIServer pid=1)     return runner.run(main)
(APIServer pid=1)            ^^^^^^^^^^^^^^^^
(APIServer pid=1)   File "/usr/lib/python3.12/asyncio/runners.py", line 118, in run
(APIServer pid=1)     return self._loop.run_until_complete(task)
(APIServer pid=1)            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1)   File "uvloop/loop.pyx", line 1518, in uvloop.loop.Loop.run_until_complete
(APIServer pid=1)   File "/usr/local/lib/python3.12/dist-packages/uvloop/__init__.py", line 48, in wrapper
(APIServer pid=1)     return await main
(APIServer pid=1)            ^^^^^^^^^^
(APIServer pid=1)   File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 670, in run_server
(APIServer pid=1)     await run_server_worker(listen_address, sock, args, **uvicorn_kwargs)
(APIServer pid=1)   File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 684, in run_server_worker
(APIServer pid=1)     async with build_async_engine_client(
(APIServer pid=1)                ^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1)   File "/usr/lib/python3.12/contextlib.py", line 210, in __aenter__
(APIServer pid=1)     return await anext(self.gen)
(APIServer pid=1)            ^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1)   File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 100, in build_async_engine_client
(APIServer pid=1)     async with build_async_engine_client_from_engine_args(
(APIServer pid=1)                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1)   File "/usr/lib/python3.12/contextlib.py", line 210, in __aenter__
(APIServer pid=1)     return await anext(self.gen)
(APIServer pid=1)            ^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1)   File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 124, in build_async_engine_client_from_engine_args
(APIServer pid=1)     vllm_config = engine_args.create_engine_config(usage_context=usage_context)
(APIServer pid=1)                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1)   File "/usr/local/lib/python3.12/dist-packages/vllm/engine/arg_utils.py", line 1967, in create_engine_config
(APIServer pid=1)     config = VllmConfig(
(APIServer pid=1)              ^^^^^^^^^^^
(APIServer pid=1)   File "/usr/local/lib/python3.12/dist-packages/pydantic/_internal/_dataclasses.py", line 121, in __init__
(APIServer pid=1)     s.__pydantic_validator__.validate_python(ArgsKwargs(args, kwargs), self_instance=s)
(APIServer pid=1)   File "/usr/local/lib/python3.12/dist-packages/vllm/config/vllm.py", line 702, in __post_init__
(APIServer pid=1)     self.quant_config = VllmConfig._get_quantization_config(
(APIServer pid=1)                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1)   File "/usr/local/lib/python3.12/dist-packages/vllm/config/vllm.py", line 529, in _get_quantization_config
(APIServer pid=1)     quant_config.maybe_update_config(model_config.model)
(APIServer pid=1)   File "/usr/local/lib/python3.12/dist-packages/vllm/model_executor/layers/quantization/quark/quark.py", line 76, in maybe_update_config
(APIServer pid=1)     quant_dtype = quant_config["global_quant_config"]["weight"]["dtype"]
(APIServer pid=1)                   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^
(APIServer pid=1) TypeError: list indices must be integers or slices, not str

I can downgrade to the vLLM version shown in other resources to work, v0.14.0, however it doesn't support KimiK25ForConditionalGeneration model architecture.

I am setting the env vars noted in the model README, however it doesn't seem to work even with AITER enabled.

Any guidance is appreciated.

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