Instructions to use 0labs-in/V1.3-CSD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use 0labs-in/V1.3-CSD with Transformers:

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

pipe = pipeline("text-generation", model="0labs-in/V1.3-CSD", 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/V1.3-CSD", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use 0labs-in/V1.3-CSD with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "0labs-in/V1.3-CSD"
# 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/V1.3-CSD",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/0labs-in/V1.3-CSD

SGLang

How to use 0labs-in/V1.3-CSD 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/V1.3-CSD" \
    --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/V1.3-CSD",
		"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/V1.3-CSD" \
        --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/V1.3-CSD",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use 0labs-in/V1.3-CSD with Docker Model Runner:
```
docker model run hf.co/0labs-in/V1.3-CSD
```

V1.3-CSD / README.md

Atharvsinh

Upload Sky v1.3 CSD checkpoint

7b713b4 verified 26 days ago

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	---
	license: other
	library_name: transformers
	pipeline_tag: text-generation
	tags:
	- sky
	- 0labs
	- csd
	- cognitive-scaffolding-decay
	- coding
	- research
	---

	# V1.3-CSD

	Sky v1.3 CSD is a 0labs research checkpoint trained with Cognitive Scaffolding Decay.

	CSD curriculum:

	1. Long scaffold examples for code understanding.
	2. Medium bridge examples for reduced explanation.
	3. Clean concise examples for daily professional coding use.

	This repository contains a standalone saved inference checkpoint and tokenizer/runtime files.

	## Research Metrics

	Training ran on an AMD MI300X.

	\| Stage \| Rows \| LR \| Train Loss \|
	\|---\|---:\|---:\|---:\|
	\| stage1_scaffold \| 915 \| 5e-7 \| 1.025 \|
	\| stage2_bridge \| 1121 \| 5e-7 \| 1.043 \|
	\| stage3_clean \| 677 \| 4e-7 \| 0.840 \|

	Quick private objective eval:

	\| Model \| Objective Score \|
	\|---\|---:\|
	\| Sky v1.3 5.5B production baseline \| 20 / 24 \|
	\| V1.3-CSD \| 22 / 24 \|

	These automatic scores are conservative checks. Rubric categories still need human or judge-model grading for paper-quality results.

	## Colab Loading Note

	Use `snapshot_download()` into a local folder before loading. This avoids dynamic module import issues caused by dots in repository names.

	```python
	from huggingface_hub import snapshot_download

	snapshot_download(
	repo_id="0labs-in/V1.3-CSD",
	local_dir="/content/sky_v1_3_csd",
	repo_type="model",
	)
	```

	Then load from `/content/sky_v1_3_csd` with `trust_remote_code=True`.