Instructions to use Harrison1213/Kimi-VL-A3B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Harrison1213/Kimi-VL-A3B-Instruct with Transformers:

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

pipe = pipeline("image-text-to-text", model="Harrison1213/Kimi-VL-A3B-Instruct", 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("Harrison1213/Kimi-VL-A3B-Instruct", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Harrison1213/Kimi-VL-A3B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Harrison1213/Kimi-VL-A3B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Harrison1213/Kimi-VL-A3B-Instruct",
		"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/Harrison1213/Kimi-VL-A3B-Instruct

SGLang

How to use Harrison1213/Kimi-VL-A3B-Instruct 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 "Harrison1213/Kimi-VL-A3B-Instruct" \
    --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": "Harrison1213/Kimi-VL-A3B-Instruct",
		"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 "Harrison1213/Kimi-VL-A3B-Instruct" \
        --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": "Harrison1213/Kimi-VL-A3B-Instruct",
		"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 Harrison1213/Kimi-VL-A3B-Instruct with Docker Model Runner:
```
docker model run hf.co/Harrison1213/Kimi-VL-A3B-Instruct
```

Kimi-VL-A3B-Instruct

File size: 2,005 Bytes

0ca6265

{
  "architectures": [
    "KimiVLForConditionalGeneration"
  ],
  "auto_map": {
    "AutoConfig": "configuration_kimi_vl.KimiVLConfig",
    "AutoModel": "modeling_kimi_vl.KimiVLForConditionalGeneration",
    "AutoModelForCausalLM": "modeling_kimi_vl.KimiVLForConditionalGeneration"
  },
  "vision_config": {
    "model_type": "moonvit",
    "patch_size": 14,
    "num_attention_heads": 16,
    "num_hidden_layers": 27,
    "hidden_size": 1152,
    "intermediate_size": 4304,
    "init_pos_emb_height": 64,
    "init_pos_emb_width": 64,
    "merge_kernel_size": [
      2,
      2
    ],
    "torch_dtype": "bfloat16"
  },
  "text_config": {
    "vocab_size": 163840,
    "max_position_embeddings": 131072,
    "hidden_size": 2048,
    "intermediate_size": 11264,
    "moe_intermediate_size": 1408,
    "num_hidden_layers": 27,
    "num_attention_heads": 16,
    "n_shared_experts": 2,
    "n_routed_experts": 64,
    "ep_size": 1,
    "routed_scaling_factor": 2.446,
    "kv_lora_rank": 512,
    "q_lora_rank": null,
    "qk_rope_head_dim": 64,
    "v_head_dim": 128,
    "qk_nope_head_dim": 128,
    "topk_method": "noaux_tc",
    "n_group": 1,
    "topk_group": 1,
    "num_experts_per_tok": 6,
    "moe_layer_freq": 1,
    "first_k_dense_replace": 1,
    "norm_topk_prob": true,
    "scoring_func": "sigmoid",
    "aux_loss_alpha": 0.001,
    "seq_aux": true,
    "num_key_value_heads": 16,
    "hidden_act": "silu",
    "initializer_range": 0.02,
    "rms_norm_eps": 1e-05,
    "pretraining_tp": 1,
    "use_cache": true,
    "rope_theta": 800000.0,
    "rope_scaling": null,
    "attention_bias": false,
    "attention_dropout": 0.0,
    "bos_token_id": 163584,
    "pad_token_id": 163839,
    "eos_token_id": 163585,
    "torch_dtype": "bfloat16",
    "tie_word_embeddings": false
  },
  "ignore_index": -100,
  "media_placeholder_token_id": 163605,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.50.3",
  "tie_word_embeddings": false,
  "vocab_size": 163840,
  "model_type": "kimi_vl"
}