Text Generation
Transformers
Safetensors
ceno
dna
genomics
dna-language-model
mamba
Mixture of Experts
custom_code
Instructions to use CladeTeam/CENO-600M-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CladeTeam/CENO-600M-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CladeTeam/CENO-600M-base", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("CladeTeam/CENO-600M-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use CladeTeam/CENO-600M-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CladeTeam/CENO-600M-base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CladeTeam/CENO-600M-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/CladeTeam/CENO-600M-base
- SGLang
How to use CladeTeam/CENO-600M-base 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 "CladeTeam/CENO-600M-base" \ --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": "CladeTeam/CENO-600M-base", "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 "CladeTeam/CENO-600M-base" \ --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": "CladeTeam/CENO-600M-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use CladeTeam/CENO-600M-base with Docker Model Runner:
docker model run hf.co/CladeTeam/CENO-600M-base
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dd63a77 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | CENO Checkpoint — CENO-600M-base
Copyright (c) 2025-2026 CENO Authors. All rights reserved.
This directory bundles a trained model checkpoint (CENO base model) together with a
copy of the CENO model code (configuration, modeling, and tokenizer modules).
The bundled model code is derived from NVIDIA's Nemotron-H HuggingFace
implementation, which is licensed under the Apache License, Version 2.0.
Nemotron-H is © NVIDIA Corporation. The CENO model code is a derivative work
distributed under the same Apache License, Version 2.0, included in this
directory as the `LICENSE` file.
The tokenizer module (`ceno_tokenizer.py`) is derived from Arc Institute's
Evo2 CharLevelTokenizer, which is licensed under the Apache License, Version 2.0.
All upstream copyright notices and license terms (NVIDIA; Arc Institute) are
preserved in the corresponding source files as required by the Apache License,
Version 2.0.
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