Instructions to use moonshotai/Kimi-VL-A3B-Thinking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use moonshotai/Kimi-VL-A3B-Thinking with Transformers:

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

pipe = pipeline("image-text-to-text", model="moonshotai/Kimi-VL-A3B-Thinking", 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("moonshotai/Kimi-VL-A3B-Thinking", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use moonshotai/Kimi-VL-A3B-Thinking with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "moonshotai/Kimi-VL-A3B-Thinking"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "moonshotai/Kimi-VL-A3B-Thinking",
		"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/moonshotai/Kimi-VL-A3B-Thinking

SGLang

How to use moonshotai/Kimi-VL-A3B-Thinking 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 "moonshotai/Kimi-VL-A3B-Thinking" \
    --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": "moonshotai/Kimi-VL-A3B-Thinking",
		"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 "moonshotai/Kimi-VL-A3B-Thinking" \
        --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": "moonshotai/Kimi-VL-A3B-Thinking",
		"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 moonshotai/Kimi-VL-A3B-Thinking with Docker Model Runner:
```
docker model run hf.co/moonshotai/Kimi-VL-A3B-Thinking
```

Kimi-VL-A3B-Thinking / tokenizer_config.json

zhouzaida

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f321730 about 1 year ago

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	{
	"added_tokens_decoder": {
	"163584": {
	"content": "[BOS]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"163585": {
	"content": "[EOS]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"163586": {
	"content": "<\|im_end\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"163601": {
	"content": "<\|im_middle\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"163587": {
	"content": "<\|im_user\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"163588": {
	"content": "<\|im_assistant\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"163594": {
	"content": "<\|im_system\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"163602": {
	"content": "<\|media_start\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"163603": {
	"content": "<\|media_content\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"163604": {
	"content": "<\|media_end\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"163605": {
	"content": "<\|media_pad\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"163838": {
	"content": "[PAD]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"163839": {
	"content": "[UNK]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	}
	},
	"additional_special_tokens": [
	"<\|im_end\|>",
	"<\|im_user\|>",
	"<\|im_assistant\|>",
	"<\|im_system\|>",
	"<\|im_middle\|>",
	"<\|media_start\|>",
	"<\|media_content\|>",
	"<\|media_end\|>",
	"<\|media_pad\|>"
	],
	"bos_token": "[BOS]",
	"clean_up_tokenization_spaces": false,
	"eos_token": "[EOS]",
	"extra_special_tokens": {},
	"model_max_length": 1048576,
	"pad_token": "[PAD]",
	"unk_token": "[UNK]",
	"tokenizer_class": "TikTokenTokenizer",
	"chat_template": "{%- for message in messages -%}{%- if loop.first and messages[0]['role'] != 'system' -%}{{'<\|im_system\|>system<\|im_middle\|>You are a helpful assistant<\|im_end\|>'}}{%- endif -%}{%- if message['role'] == 'system' -%}{{'<\|im_system\|>'}}{%- endif -%}{%- if message['role'] == 'user' -%}{{'<\|im_user\|>'}}{%- endif -%}{%- if message['role'] == 'assistant' -%}{{'<\|im_assistant\|>'}}{%- endif -%}{{- message['role'] -}}{{'<\|im_middle\|>'}}{%- if message['content'] is string -%}{{- message['content'] + '<\|im_end\|>' -}}{%- else -%}{%- for content in message['content'] -%}{%- if content['type'] == 'image' or 'image' in content or 'image_url' in content -%}{{'<\|media_start\|>image<\|media_content\|><\|media_pad\|><\|media_end\|>'}}{%- else -%}{{content['text']}}{%- endif -%}{%- endfor -%}{{'<\|im_end\|>'}}{%- endif -%}{%- endfor -%}{%- if add_generation_prompt -%}{{'<\|im_assistant\|>assistant<\|im_middle\|>'}}{%- endif -%}",
	"auto_map": {
	"AutoTokenizer": [
	"tokenization_moonshot.TikTokenTokenizer",
	null
	]
	}
	}