knox / Llama-Deployment-6.sh
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| 1 | python3 -m venv venv |
| 2 | source venv/bin/activate |
knox / Llama-Deployment-5.sh
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| 1 | cd ~ |
| 2 | git clone https://github.com/ollama/llama.git |
| 3 | cd llama |
knox / Llama-Deployment-4.sh
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| 1 | sudo apt install -y python3 python3-pip python3-venv git curl |
knox / Llama-Deployment-3.sh
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| 1 | su - deployer |
knox / Llama-Deployment-2.sh
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| 1 | sudo adduser deployer |
| 2 | sudo usermod -aG sudo deployer |
knox / Llama-Deployment-1.sh
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| 1 | sudo apt update && sudo apt upgrade -y |
knox / LLaMA-Factory-22.bib
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| 1 | @inproceedings{zheng2024llamafactory, |
| 2 | title={LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models}, |
| 3 | author={Yaowei Zheng and Richong Zhang and Junhao Zhang and Yanhan Ye and Zheyan Luo and Zhangchi Feng and Yongqiang Ma}, |
| 4 | booktitle={Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)}, |
| 5 | address={Bangkok, Thailand}, |
| 6 | publisher={Association for Computational Linguistics}, |
| 7 | year={2024}, |
| 8 | url={http://arxiv.org/abs/2403.13372} |
| 9 | } |
knox / LLaMA-Factory-21.yaml
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| 1 | report_to: wandb |
| 2 | run_name: test_run # optional |
knox / LLaMA-Factory-20.sh
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| 1 | export USE_OPENMIND_HUB=1 # `set USE_OPENMIND_HUB=1` for Windows |
knox / LLaMA-Factory-19.sh
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| 1 | export USE_MODELSCOPE_HUB=1 # `set USE_MODELSCOPE_HUB=1` for Windows |