Instructions to use SC117/Ornith-1.0-9B-heretic-MTP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SC117/Ornith-1.0-9B-heretic-MTP with Transformers:

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

pipe = pipeline("text-generation", model="SC117/Ornith-1.0-9B-heretic-MTP")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForCausalLM

processor = AutoProcessor.from_pretrained("SC117/Ornith-1.0-9B-heretic-MTP")
model = AutoModelForCausalLM.from_pretrained("SC117/Ornith-1.0-9B-heretic-MTP", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use SC117/Ornith-1.0-9B-heretic-MTP with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SC117/Ornith-1.0-9B-heretic-MTP"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SC117/Ornith-1.0-9B-heretic-MTP",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/SC117/Ornith-1.0-9B-heretic-MTP

SGLang

How to use SC117/Ornith-1.0-9B-heretic-MTP 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 "SC117/Ornith-1.0-9B-heretic-MTP" \
    --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": "SC117/Ornith-1.0-9B-heretic-MTP",
		"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 "SC117/Ornith-1.0-9B-heretic-MTP" \
        --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": "SC117/Ornith-1.0-9B-heretic-MTP",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use SC117/Ornith-1.0-9B-heretic-MTP with Docker Model Runner:
```
docker model run hf.co/SC117/Ornith-1.0-9B-heretic-MTP
```

SC117 commited on Jun 29

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@@ -145,7 +145,7 @@ For GGUF quantized versions (Q8_0, Q6_K, Q4_K_M), see: [SC117/Ornith-1.0-9B-here
 - **Original Model**: https://huggingface.co/deepreinforce-ai/Ornith-1.0-9B
 - **Ornith Blog**: https://deep-reinforce.com/ornith.html
-- **heretic Abliteration**: https://github.com/kabachuha/heretic
 - **BenchLocal Results**: https://scorp1o117.github.io/benchlocal-results/
 ## Citation

 - **Original Model**: https://huggingface.co/deepreinforce-ai/Ornith-1.0-9B
 - **Ornith Blog**: https://deep-reinforce.com/ornith.html
+- **heretic Abliteration**: https://github.com/p-e-w/heretic
 - **BenchLocal Results**: https://scorp1o117.github.io/benchlocal-results/
 ## Citation