Text Generation
Transformers
Safetensors
French
English
Chinese
deepseek_v4
cortex
code-generation
web-development
software-engineering
Mixture of Experts
8-bit precision
fp8
Instructions to use Frankenstein-Labs/cortex.6.sol with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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
Commit History
22 days ago
-
docs(cortex): center public presentation on CORTEX and Frankenstein-Labs
openhands +1: openhandsRewrite the model card around CORTEX as the product: identity block (Model/Developer/Focus), the ten capabilities, an international vision section and the founder's statement. The base model and its legal attribution stay in a dedicated provenance/license section instead of the opening. No technical claim was changed; parameter counts, context size, quantization and the unverified-checkpoint disclaimer are intact. Co-authored-by: openhands <openhands@all-hands.dev>f7ae039
29 days ago
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feat: update creator identity attribution
43fd0d0
30 days ago
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feat(cortex-ai): agent engine, tool registry, OpenAI-compatible API, fine-tuning pipeline
Adds the CORTEX AI ecosystem layer on top of the base model. - cortex_ai/config.py configuration, environment overrides, validation - cortex_ai/tools/ tool registry with JSON-schema validation - cortex_ai/engine/ agent loop + DSML completion builders - cortex_ai/adapters/ unified model interface (mock and Hugging Face) - cortex_ai/api/ OpenAI-compatible HTTP API - cortex_ai/client.py dependency-free Python client - cortex_ai/training/ dataset pipeline, LoRA config, training entry point - docs/ French guides: architecture, API, fine-tuning - data/cortex_sft.jsonl 10-example French instruction dataset - tests/ 58 new tests Verified on a 4-core CPU machine with no GPU: the full agent loop (encode -> model -> parse -> tool -> reinject -> answer), the real HTTP API queried with curl and with the client, and the dataset pipeline validated against the real encoder. All 58 new tests pass. Not verified: load…c63bc31 -
docs(cortex-ai): correct provenance attribution and add French documentation
- name deepseek-ai/DeepSeek-V4-Pro-0813 as the upstream model and DeepSeek-AI as its author, replacing the incorrect Cortex-ai attribution in the provenance table - fix the copyright notice to match the retained LICENSE file (2023 DeepSeek) - replace the two dead upstream links with the working vLLM and SGLang pages - restore the real architecture name (DeepseekV4ForCausalLM / deepseek_v4) - restore the upstream BibTeX entry - rewrite the model card in French, centred on the CORTEX AI project - reword identity.py so the system prompt no longer claims the base model was created by Frankenstein-Labs; also fix accent/apostrophe matching in is_identity_question, which previously failed on 'Qui t a cree ?' - add docs/: getting started, message encoding and tool calling, distributed inference, and the real state of the vision layer The weight files are unchanged.2763f1c