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
File size: 625 Bytes
dd63a77 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | {
"tokenizer_class": "CENOCharLevelTokenizer",
"vocab_size": 512,
"eos_token": "<eos>",
"pad_token": "<pad>",
"unk_token": "<unk>",
"eod_id": 0,
"eos_id": 0,
"pad_id": 1,
"unk_id": 2,
"model_max_length": 1000000000000000019884624838656,
"clean_up_tokenization_spaces": true,
"tokenize_chinese_chars": false,
"strip_accents": null,
"do_lower_case": false,
"do_basic_tokenize": false,
"never_split": null,
"tokenizer_type": "CharLevelTokenizer",
"name_or_path": "./ceno_tokenizer",
"auto_map": {
"AutoTokenizer": [
"ceno_tokenizer.CENOCharLevelTokenizer",
null
]
}
}
|