Instructions to use llmware/slim-summary-tiny-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use llmware/slim-summary-tiny-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="llmware/slim-summary-tiny-onnx")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("llmware/slim-summary-tiny-onnx") model = AutoModelForCausalLM.from_pretrained("llmware/slim-summary-tiny-onnx") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use llmware/slim-summary-tiny-onnx with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "llmware/slim-summary-tiny-onnx" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "llmware/slim-summary-tiny-onnx", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/llmware/slim-summary-tiny-onnx
- SGLang
How to use llmware/slim-summary-tiny-onnx 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 "llmware/slim-summary-tiny-onnx" \ --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": "llmware/slim-summary-tiny-onnx", "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 "llmware/slim-summary-tiny-onnx" \ --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": "llmware/slim-summary-tiny-onnx", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use llmware/slim-summary-tiny-onnx with Docker Model Runner:
docker model run hf.co/llmware/slim-summary-tiny-onnx
Update config.json
Browse files- config.json +1 -1
config.json
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"tokenizer_config": {"bos_id":[1], "bos_token":["<s>"], "eos_id":[2],"eos_token":["</s>"]},
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"model_parent": "llmware/slim-summary-tiny",
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"quantization": "int4",
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"model_family": "
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"parameters": 1.1,
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"publisher": "llmware",
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"release_date": "september 2024",
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"tokenizer_config": {"bos_id":[1], "bos_token":["<s>"], "eos_id":[2],"eos_token":["</s>"]},
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"model_parent": "llmware/slim-summary-tiny",
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"quantization": "int4",
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"model_family": "ONNXGenerativeModel",
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"parameters": 1.1,
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"publisher": "llmware",
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"release_date": "september 2024",
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