Instructions to use antheticplus-studios/Genesis-550-Core with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use antheticplus-studios/Genesis-550-Core with Transformers:

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

pipe = pipeline("text-generation", model="antheticplus-studios/Genesis-550-Core")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("antheticplus-studios/Genesis-550-Core", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use antheticplus-studios/Genesis-550-Core with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "antheticplus-studios/Genesis-550-Core"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "antheticplus-studios/Genesis-550-Core",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/antheticplus-studios/Genesis-550-Core

SGLang

How to use antheticplus-studios/Genesis-550-Core 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 "antheticplus-studios/Genesis-550-Core" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "antheticplus-studios/Genesis-550-Core",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "antheticplus-studios/Genesis-550-Core" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "antheticplus-studios/Genesis-550-Core",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use antheticplus-studios/Genesis-550-Core with Docker Model Runner:
```
docker model run hf.co/antheticplus-studios/Genesis-550-Core
```

antheticplus-studios commited on Sep 21

Commit

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+---
+license: apache-2.0
+language:
+- en
+tags:
+- AntheticPlus-Studios
+- Smyight
+- Genesis-550-Core
+- text-generation
+- code-generation
+- directory-synthesis
+---
+# Genesis-550 Core
+Developed by **AntheticPlus Studios**
+Engineered & Created by **Smyight**
+## Model Overview
+Genesis-550 Core is a proprietary 550-billion parameter Mixture-of-Experts cognitive AI engine. It is optimized for multi-step architectural reasoning, full-stack code synthesis, physical root directory file management, and dynamic image rendering hooks.
+## Core Architecture & Capabilities
+- **Engine Architecture:** 550B Parameter MoE Cognitive Layer
+- **Context Window:** 1,000,000 Tokens
+- **Directory Synthesis:** Generates complete project folder systems in valid JSON trees.
+- **Design System:** Advanced UI/UX layout, modern CSS, and component synthesis.
+- **Cognitive Engine:** Self-directed reasoning, verification tagging, and risk placement.
+## Master System Prompt
+The model is aligned to run using `system_prompt.txt` included in this repository.