Instructions to use apple/OpenELM-3B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apple/OpenELM-3B-Instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="apple/OpenELM-3B-Instruct", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("apple/OpenELM-3B-Instruct", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use apple/OpenELM-3B-Instruct with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "apple/OpenELM-3B-Instruct" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "apple/OpenELM-3B-Instruct", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/apple/OpenELM-3B-Instruct
- SGLang
How to use apple/OpenELM-3B-Instruct 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 "apple/OpenELM-3B-Instruct" \ --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": "apple/OpenELM-3B-Instruct", "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 "apple/OpenELM-3B-Instruct" \ --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": "apple/OpenELM-3B-Instruct", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use apple/OpenELM-3B-Instruct with Docker Model Runner:
docker model run hf.co/apple/OpenELM-3B-Instruct
Update generate_openelm.py
Browse files- generate_openelm.py +2 -2
generate_openelm.py
CHANGED
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@@ -217,7 +217,7 @@ if __name__ == '__main__':
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args = openelm_generate_parser()
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prompt = args.prompt
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-
output_text,
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prompt=prompt,
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model=args.model,
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device=args.device,
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@@ -234,7 +234,7 @@ if __name__ == '__main__':
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f'{output_text}\r\n'
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f'{"-" * os.get_terminal_size().columns}\r\n'
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'\r\nGeneration took'
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f'\033[1m\033[92m {round(
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'seconds.\r\n'
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)
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print(print_txt)
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args = openelm_generate_parser()
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prompt = args.prompt
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+
output_text, generation_time = generate(
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prompt=prompt,
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model=args.model,
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device=args.device,
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f'{output_text}\r\n'
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f'{"-" * os.get_terminal_size().columns}\r\n'
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'\r\nGeneration took'
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+
f'\033[1m\033[92m {round(generation_time, 2)} \033[0m'
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'seconds.\r\n'
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)
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print(print_txt)
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