Instructions to use DarkArtsForge/Magistaroth-24B-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DarkArtsForge/Magistaroth-24B-v1 with Transformers:

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

pipe = pipeline("text-generation", model="DarkArtsForge/Magistaroth-24B-v1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DarkArtsForge/Magistaroth-24B-v1")
model = AutoModelForCausalLM.from_pretrained("DarkArtsForge/Magistaroth-24B-v1", device_map="auto")
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 Settings

vLLM

How to use DarkArtsForge/Magistaroth-24B-v1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DarkArtsForge/Magistaroth-24B-v1"
# 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/Magistaroth-24B-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/DarkArtsForge/Magistaroth-24B-v1

SGLang

How to use DarkArtsForge/Magistaroth-24B-v1 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/Magistaroth-24B-v1" \
    --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/Magistaroth-24B-v1",
		"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/Magistaroth-24B-v1" \
        --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/Magistaroth-24B-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use DarkArtsForge/Magistaroth-24B-v1 with Docker Model Runner:
```
docker model run hf.co/DarkArtsForge/Magistaroth-24B-v1
```

Magistaroth-24B-v1 / README.md

Naphula

Create README.md

8ec14b7 verified 7 months ago

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metadata

license: apache-2.0
base_model:
  - mistralai/Magistral-Small-2509
  - Gryphe/Tiamat-24B-Magistral
  - TheDrummer/Magidonia-24B-v4.3
  - TheDrummer/Precog-24B-v1
  - zerofata/MS3.2-PaintedFantasy-v3-24B
  - zerofata/MS3.2-PaintedFantasy-v4.1-24B
datasets:
  - OccultAI/illuminati_imatrix_v1
language:
  - en
library_name: transformers
tags:
  - DELLA
  - merge
  - mergekit
widget:
  - text: Magistaroth 24B v1
    output:
      url: >-
        https://cdn-uploads.huggingface.co/production/uploads/68e840caa318194c44ec2a04/n2QI4o6Xx2d5QUhsLvmt3.png

⚠️ Warning: This model can produce narratives and RP that contain violent and graphic erotic content. Adjust your system prompt accordingly, and use Mistral Tekken chat template.

🌌 Magistaroth 24B v1

A highly creative merge. Some refusals but you can use jailbreaks or ablate the model. A normtrue version was tested. Normfalse did better overall, it was slightly less censored, more detailed and creative.

Scores 14152 at Q0 Bench (Pass Q0G).

This model was merged using the following merge method: DELLA

architecture: MistralForCausalLM
models:
  - model: B:\24B\!models--mistralai--Magistral-Small-2509\textonly
  - model: B:\24B\!models--Gryphe--Tiamat-24B-Magistral\textonly
    parameters:
      density: 0.9
      weight: 0.4
      epsilon: 0.099
  - model: B:\24B\!models--TheDrummer--Magidonia-24B-v4.3
    parameters:
      density: 0.9
      weight: 0.4
      epsilon: 0.099
  - model: B:\24B\!models--TheDrummer--Precog-24B-v1
    parameters:
      density: 0.9
      weight: 0.4
      epsilon: 0.099
  - model: B:\24B\!models--zerofata--MS3.2-PaintedFantasy-v3-24B
    parameters:
      density: 0.9
      weight: 0.4
      epsilon: 0.099
  - model: B:\24B\!models--zerofata--MS3.2-PaintedFantasy-v4.1-24B
    parameters:
      density: 0.9
      weight: 0.4
      epsilon: 0.099
# Seed: 420
merge_method: della
base_model: B:\24B\!models--mistralai--Magistral-Small-2509\textonly
parameters:
  lambda: 1.0
  normalize: false
  int8_mask: false
dtype: float32
out_dtype: bfloat16
tokenizer:
  source: B:\24B\!models--TheDrummer--Magidonia-24B-v4.3
# chat_template: auto
name: 🌌 Magistaroth-24B-v1