Instructions to use tiny-random/kimi-k3.1-pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tiny-random/kimi-k3.1-pro with Transformers:

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

pipe = pipeline("image-text-to-text", model="tiny-random/kimi-k3.1-pro", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForSeq2SeqLM
model = AutoModelForSeq2SeqLM.from_pretrained("tiny-random/kimi-k3.1-pro", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use tiny-random/kimi-k3.1-pro with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tiny-random/kimi-k3.1-pro"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tiny-random/kimi-k3.1-pro",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/tiny-random/kimi-k3.1-pro

SGLang

How to use tiny-random/kimi-k3.1-pro 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 "tiny-random/kimi-k3.1-pro" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tiny-random/kimi-k3.1-pro",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "tiny-random/kimi-k3.1-pro" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tiny-random/kimi-k3.1-pro",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use tiny-random/kimi-k3.1-pro with Docker Model Runner:
```
docker model run hf.co/tiny-random/kimi-k3.1-pro
```

yujiepan commited on about 19 hours ago

Commit

df7a0f1

verified ·

1 Parent(s): 8b67a47

Upload folder using huggingface_hub

Browse files

Files changed (2) hide show

.meta/create_model.py +1 -1
model.safetensors +2 -2

.meta/create_model.py CHANGED Viewed

@@ -350,5 +350,5 @@ def create_model(source_model_id: str, source_revision: str, save_folder: str) -
 create_model(
     source_model_id="moonshotai/Kimi-K3.1-Pro",
     source_revision="d9e99b0792a5e93b78ea9bea62a68167e36ddd9e",
-    save_folder="/tmp/kimi-k31-v2",
 )

 create_model(
     source_model_id="moonshotai/Kimi-K3.1-Pro",
     source_revision="d9e99b0792a5e93b78ea9bea62a68167e36ddd9e",
+    save_folder="/tmp/kimi-k3.1-pro",
 )

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:35842b8a041956803e5ea97e515fe0463a22a4e8b5ec1a5151868af0bebfd4be
-size 35578920

 version https://git-lfs.github.com/spec/v1
+oid sha256:ac374bbdaa96d2f421c37acfeaeefb029ae9acee6f9b2a3bbbc0ebddbc8c428f
+size 35577384