Instructions to use amd/AMD-OLMo-1B-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amd/AMD-OLMo-1B-SFT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="amd/AMD-OLMo-1B-SFT")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("amd/AMD-OLMo-1B-SFT") model = AutoModelForCausalLM.from_pretrained("amd/AMD-OLMo-1B-SFT") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use amd/AMD-OLMo-1B-SFT with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "amd/AMD-OLMo-1B-SFT" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "amd/AMD-OLMo-1B-SFT", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/amd/AMD-OLMo-1B-SFT
- SGLang
How to use amd/AMD-OLMo-1B-SFT 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 "amd/AMD-OLMo-1B-SFT" \ --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": "amd/AMD-OLMo-1B-SFT", "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 "amd/AMD-OLMo-1B-SFT" \ --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": "amd/AMD-OLMo-1B-SFT", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use amd/AMD-OLMo-1B-SFT with Docker Model Runner:
docker model run hf.co/amd/AMD-OLMo-1B-SFT
Update README.md
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README.md
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| **AlpacaEval 2 (LC Win Rate)** | Length Control Win Rate (weighted_alpaca_eval_gpt4_turbo) |
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| **MTBench** | Average score for single-answer grading (2 turns) |
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#### License
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Copyright (c) 2018-2024 Advanced Micro Devices, Inc. All Rights Reserved.
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| **AlpacaEval 2 (LC Win Rate)** | Length Control Win Rate (weighted_alpaca_eval_gpt4_turbo) |
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| **MTBench** | Average score for single-answer grading (2 turns) |
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Feel free to cite our AMD-OLMo models:
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```bash
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@misc{AMD-OLMo,
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title = {AMD-OLMo: A series of 1B language models trained from scratch by AMD on AMD Instinct™ MI250 GPUs.},
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url = {https://huggingface.co/amd/AMD-OLMo},
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author = {Jiang Liu, Jialian Wu, Prakamya Mishra, Zicheng Liu, Sudhanshu Ranjan, Pratik Prabhanjan Brahma, Yusheng Su, Gowtham Ramesh, Peng Sun, Zhe Li, Dong Li, Lu Tian, Emad Barsoum},
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month = {October},
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year = {2024}
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}
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```
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#### License
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Copyright (c) 2018-2024 Advanced Micro Devices, Inc. All Rights Reserved.
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