Instructions to use 0labs-in/Sky-v2.0-11B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use 0labs-in/Sky-v2.0-11B with Transformers:

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

pipe = pipeline("text-generation", model="0labs-in/Sky-v2.0-11B", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("0labs-in/Sky-v2.0-11B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use 0labs-in/Sky-v2.0-11B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "0labs-in/Sky-v2.0-11B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "0labs-in/Sky-v2.0-11B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/0labs-in/Sky-v2.0-11B

SGLang

How to use 0labs-in/Sky-v2.0-11B 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 "0labs-in/Sky-v2.0-11B" \
    --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": "0labs-in/Sky-v2.0-11B",
		"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 "0labs-in/Sky-v2.0-11B" \
        --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": "0labs-in/Sky-v2.0-11B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use 0labs-in/Sky-v2.0-11B with Docker Model Runner:
```
docker model run hf.co/0labs-in/Sky-v2.0-11B
```

Sky-v2.0-11B / benchmarks.json

Atharvsinh

Sky v2.0 — CREST 11B (adaptive-depth reasoning)

4bbb59c verified 21 days ago

raw

history blame contribute delete

408 Bytes

	{
	"code_eval": {
	"passed": 25,
	"total": 25,
	"accuracy": 100.0
	},
	"mmlu_pro_200": {
	"correct": 91,
	"total": 200,
	"accuracy": 45.5
	},
	"identity": "Sky v2.0 / 0labs / Atharvsinh Jadav",
	"architecture": "CREST (4 steps, adaptive halting)",
	"base_model": "Qwen/Qwen3.5-4B",
	"total_params": "11.00B",
	"training_time": "2.3 hours",
	"hardware": "AMD MI300X (205GB VRAM)"
	}