Instructions to use Vortex5/Nether-Moon-12B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Vortex5/Nether-Moon-12B with Transformers:

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

pipe = pipeline("text-generation", model="Vortex5/Nether-Moon-12B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Vortex5/Nether-Moon-12B")
model = AutoModelForCausalLM.from_pretrained("Vortex5/Nether-Moon-12B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.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(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Vortex5/Nether-Moon-12B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Vortex5/Nether-Moon-12B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Vortex5/Nether-Moon-12B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Vortex5/Nether-Moon-12B

SGLang

How to use Vortex5/Nether-Moon-12B 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 "Vortex5/Nether-Moon-12B" \
    --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": "Vortex5/Nether-Moon-12B",
		"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 "Vortex5/Nether-Moon-12B" \
        --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": "Vortex5/Nether-Moon-12B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Vortex5/Nether-Moon-12B with Docker Model Runner:
```
docker model run hf.co/Vortex5/Nether-Moon-12B
```

It's really great !

by sphfs - opened about 16 hours ago

Discussion

sphfs

about 16 hours ago

I've try multiple 12B models (seriously i downloaded around 150GB worth of i1-Q4_K_M 12B models) and few come close to this one for now !

(I didn't test everything since it's getting quite late for me but from what i could test it's amazing !)

(I've used the Q4_K_S quants since that was the only thing available at the time. )

Vortex5

Owner about 15 hours ago

Thank you! I am happy to hear it!

unknown2304

about 15 hours ago

I have the same first impression. One thing to note is that the chars are not going out of character as much as they used to with the other 12B models. Really good job here, no formatting issues with ChatML template. Morbid-Miasma-12B has repetitive issues with my settings, but this one is just perfect after 2-3 hours. Thanks!

Vortex5

Owner about 11 hours ago

Thank you! Glad you like it!

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