Instructions to use DarkArtsForge/Protocol-Phantom-12B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DarkArtsForge/Protocol-Phantom-12B with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DarkArtsForge/Protocol-Phantom-12B")
model = AutoModelForCausalLM.from_pretrained("DarkArtsForge/Protocol-Phantom-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]:]))

NeMo
How to use DarkArtsForge/Protocol-Phantom-12B with NeMo:
```
# tag did not correspond to a valid NeMo domain.
```
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use DarkArtsForge/Protocol-Phantom-12B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DarkArtsForge/Protocol-Phantom-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": "DarkArtsForge/Protocol-Phantom-12B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/DarkArtsForge/Protocol-Phantom-12B

SGLang

How to use DarkArtsForge/Protocol-Phantom-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 "DarkArtsForge/Protocol-Phantom-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": "DarkArtsForge/Protocol-Phantom-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 "DarkArtsForge/Protocol-Phantom-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": "DarkArtsForge/Protocol-Phantom-12B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use DarkArtsForge/Protocol-Phantom-12B with Docker Model Runner:
```
docker model run hf.co/DarkArtsForge/Protocol-Phantom-12B
```

Protocol-Phantom-12B / README.md

Naphula

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	---
	base_model:
	- mistralai/Mistral-Nemo-Instruct-2407
	- LatitudeGames/Wayfarer-2-12B
	- WokeAI/Tankie-DPE-12B-SFT-v2
	library_name: transformers
	tags:
	- mergekit
	- merge
	- mistral
	- nemo
	- nuslerp
	widget:
	- text: "Protocol-Phantom-12B"
	output:
	url: https://cdn-uploads.huggingface.co/production/uploads/68e840caa318194c44ec2a04/3kDEO5re1fpIasFVmJeeK.png
	---

	> [!CAUTION]
	> <span style="color:red; font-weight:bold">⚠️ Warning:</span> This model can produce narratives and RP that contain violent and graphic erotic content. Adjust your system prompt accordingly, and use ChatML chat template.
	>

	# 🧞‍ Protocol Phantom 12B

	![Protocol_Phantom](https://cdn-uploads.huggingface.co/production/uploads/68e840caa318194c44ec2a04/3kDEO5re1fpIasFVmJeeK.png)

	This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

	This model was merged using the [nuslerp](https://github.com/arcee-ai/mergekit/blob/main/docs/merge_methods.md) method using mistralai/Mistral-Nemo-Instruct-2407 as a base.

	Protocol Phantom has some refusals and may require jailbreaks or ablation to fully uncensor.

	Several methods were tested including `karcher` and `della`, but they produced broken output. Models such as Impish Bloodmoon, SakuraKaze, Irix, VelvetCafe, Arsenic Shahrazad, and others had to be omitted from the merge.

	### Configuration

	The following YAML configuration was used to produce this model:

	```yaml
	architecture: MistralForCausalLM
	base_model: B:/12B/mistralai--Mistral-Nemo-Instruct-2407
	models:
	- model: B:/12B/LatitudeGames--Wayfarer-2-12B
	parameters:
	weight: 0.5
	- model: B:/12B/WokeAI--Tankie-DPE-12b-SFT-v2
	parameters:
	weight: 0.5
	merge_method: nuslerp
	parameters:
	nuslerp_flatten: false # Flattens tensors to treat them as high-dimensional vectors
	nuslerp_row_wise: true # Set to true if you want to interpolate per-row instead of per-tensor
	dtype: float32
	out_dtype: bfloat16
	tokenizer:
	source: union
	```