Instructions to use Frankenstein-Labs/cortex.6.sol with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Frankenstein-Labs/cortex.6.sol with Transformers:

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

pipe = pipeline("text-generation", model="Frankenstein-Labs/cortex.6.sol")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Frankenstein-Labs/cortex.6.sol")
model = AutoModelForCausalLM.from_pretrained("Frankenstein-Labs/cortex.6.sol", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Frankenstein-Labs/cortex.6.sol with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Frankenstein-Labs/cortex.6.sol"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Frankenstein-Labs/cortex.6.sol",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Frankenstein-Labs/cortex.6.sol

SGLang

How to use Frankenstein-Labs/cortex.6.sol 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 "Frankenstein-Labs/cortex.6.sol" \
    --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": "Frankenstein-Labs/cortex.6.sol",
		"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 "Frankenstein-Labs/cortex.6.sol" \
        --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": "Frankenstein-Labs/cortex.6.sol",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Frankenstein-Labs/cortex.6.sol with Docker Model Runner:
```
docker model run hf.co/Frankenstein-Labs/cortex.6.sol
```

cortex.6.sol / checkpoints /README.md

openhands

feat(cortex): add CORTEX training pipeline and model audit

6fbe100 20 days ago

preview code

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CORTEX — checkpoints

Ce dossier contient les checkpoints produits par Frankenstein-Labs.

Rien n'y est versionné : les checkpoints sont des artefacts reproductibles, pas du code. .gitignore exclut *.pt, *.safetensors et le contenu de ce dossier.

Structure d'un checkpoint

checkpoints/dev/
    step-500/
        config.json         hyper-paramètres du modèle
        weights.safetensors
        provenance.json     développeur, base_model, datasets, configuration
        manifest.json       tailles et SHA-256 de chaque fichier
    final/
        ...

Vérification

from model.init import load_cortex_checkpoint

model, config, provenance = load_cortex_checkpoint("checkpoints/dev/final")
print(config.model_name, provenance["step"], provenance["parameter_count"])

load_cortex_checkpoint() recalcule le SHA-256 de chaque fichier listé dans le manifeste et refuse le checkpoint si un fichier manque, change de taille ou est corrompu.

Distinction à conserver

Un checkpoint de ce dossier est un modèle entraîné par Frankenstein-Labs. Il n'a aucun lien de dérivation avec les 66 shards distribués dans ce dépôt, qui proviennent de DeepSeek-AI et restent inchangés. Le champ base_model de provenance.json vaut null tant que c'est le cas.

Voir docs/pipeline-cortex.fr.md pour l'état réel du pipeline.