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

Libraries

How to use moonshotai/Kimi-K2-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="moonshotai/Kimi-K2-Instruct", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("moonshotai/Kimi-K2-Instruct", trust_remote_code=True, dtype="auto")

Inference
HuggingChat
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use moonshotai/Kimi-K2-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "moonshotai/Kimi-K2-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": "moonshotai/Kimi-K2-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/moonshotai/Kimi-K2-Instruct

SGLang

How to use moonshotai/Kimi-K2-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 "moonshotai/Kimi-K2-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": "moonshotai/Kimi-K2-Instruct",
		"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 "moonshotai/Kimi-K2-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": "moonshotai/Kimi-K2-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use moonshotai/Kimi-K2-Instruct with Docker Model Runner:
```
docker model run hf.co/moonshotai/Kimi-K2-Instruct
```

Update

#44

by reactkick - opened Aug 3, 2025

base: refs/heads/main

←

from: refs/pr/44

Discussion Files changed

+39

-1

Files changed (1) hide show

README.md +39 -1

README.md CHANGED Viewed

@@ -2,6 +2,44 @@
 license: other
 license_name: modified-mit
 library_name: transformers
 ---
 <div align="center">
   <picture>
@@ -800,4 +838,4 @@ See [THIRD PARTY NOTICES](THIRD_PARTY_NOTICES.md)
 ## 7. Contact Us
-If you have any questions, please reach out at [support@moonshot.cn](mailto:support@moonshot.cn).

 license: other
 license_name: modified-mit
 library_name: transformers
+datasets:
+- fka/awesome-chatgpt-prompts
+- Kratos-AI/KAI_handwriting-ocr
+language:
+- tr
+- ar
+- en
+metrics:
+- accuracy
+- bertscore
+- bleu
+- bleurt
+- brier_score
+- cer
+- character
+- charcut_mt
+base_model:
+- moonshotai/Kimi-K2-Instruct
+- Chain-GPT/Solidity-LLM
+- HuggingFaceTB/SmolLM3-3B
+- zai-org/GLM-4.1V-9B-Thinking
+- DevQuasar/zai-org.GLM-4.1V-9B-Base-GGUF
+- black-forest-labs/FLUX.1-Kontext-dev
+- mistralai/Voxtral-Mini-3B-2507
+- Qwen/Qwen3-Coder-480B-A35B-Instruct
+- ChatDOC/OCRFlux-3B
+new_version: moonshotai/Kimi-K2-Instruct
+pipeline_tag: zero-shot-classification
+tags:
+- text-generation-inference
+- medical
+- climate
+- merge
+- code
+- art
+- legal
+- biology
+- chemistry
 ---
 <div align="center">
   <picture>
 ## 7. Contact Us
+If you have any questions, please reach out at [support@moonshot.cn](mailto:support@moonshot.cn).