Instructions to use RadixArk/Inkling-DSpark-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use RadixArk/Inkling-DSpark-Preview with Transformers:

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

pipe = pipeline("text-generation", model="RadixArk/Inkling-DSpark-Preview", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("RadixArk/Inkling-DSpark-Preview", trust_remote_code=True)
model = AutoModel.from_pretrained("RadixArk/Inkling-DSpark-Preview", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use RadixArk/Inkling-DSpark-Preview with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/RadixArk/Inkling-DSpark-Preview

SGLang

How to use RadixArk/Inkling-DSpark-Preview 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 "RadixArk/Inkling-DSpark-Preview" \
    --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": "RadixArk/Inkling-DSpark-Preview",
		"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 "RadixArk/Inkling-DSpark-Preview" \
        --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": "RadixArk/Inkling-DSpark-Preview",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use RadixArk/Inkling-DSpark-Preview with Docker Model Runner:
```
docker model run hf.co/RadixArk/Inkling-DSpark-Preview
```

skx618 commited on 1 day ago

Commit

ea0ac69

verified ·

1 Parent(s): 663e994

Update README.md

Browse files

Files changed (1) hide show

README.md +1 -2

README.md CHANGED Viewed

@@ -49,11 +49,10 @@ Acceptance length (`acc_len`) at temperature 0:
 ## Serving with SGLang
-Requires a SGLang build with DSpark support:
 ```bash
 SGLANG_ENABLE_UNIFIED_RADIX_TREE=1 \
-SGLANG_INKLING_DEFAULT_REASONING_EFFORT=0.99 \
 python -m sglang.launch_server \
   --trust-remote-code \
   --model-path thinkingmachines/Inkling-NVFP4 \

 ## Serving with SGLang
+Requires a SGLang build (`docker pull lmsysorg/sglang:dev-cu13-inkling-dspark`) with DSpark support:
 ```bash
 SGLANG_ENABLE_UNIFIED_RADIX_TREE=1 \
 python -m sglang.launch_server \
   --trust-remote-code \
   --model-path thinkingmachines/Inkling-NVFP4 \