Instructions to use aduncan94/EnhancAR-Sorted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aduncan94/EnhancAR-Sorted with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="aduncan94/EnhancAR-Sorted")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("aduncan94/EnhancAR-Sorted") model = AutoModelForCausalLM.from_pretrained("aduncan94/EnhancAR-Sorted") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use aduncan94/EnhancAR-Sorted with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "aduncan94/EnhancAR-Sorted" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aduncan94/EnhancAR-Sorted", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/aduncan94/EnhancAR-Sorted
- SGLang
How to use aduncan94/EnhancAR-Sorted 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 "aduncan94/EnhancAR-Sorted" \ --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": "aduncan94/EnhancAR-Sorted", "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 "aduncan94/EnhancAR-Sorted" \ --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": "aduncan94/EnhancAR-Sorted", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use aduncan94/EnhancAR-Sorted with Docker Model Runner:
docker model run hf.co/aduncan94/EnhancAR-Sorted
File size: 961 Bytes
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"added_tokens_decoder": {
"6": {
"content": "!",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false,
"special": true
},
"7": {
"content": "*",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false,
"special": true
},
"8": {
"content": "/",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false,
"special": true
},
"9": {
"content": "@",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false,
"special": true
}
},
"auto_map": {
"AutoTokenizer": [
"tokenizers.DNATokenizer",
null
]
},
"bos_token": "@",
"clean_up_tokenization_spaces": true,
"eos_token": "*",
"model_max_length": 2048,
"pad_token": "!",
"sep_token": "/",
"tokenizer_class": "DNATokenizer"
} |