Instructions to use emilykang/Phi_medner-soap_chart_progressnotes_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use emilykang/Phi_medner-soap_chart_progressnotes_lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2") model = PeftModel.from_pretrained(base_model, "emilykang/Phi_medner-soap_chart_progressnotes_lora") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from emilykang/Phi_medner-soap_chart_progressnotes_lora: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/emilykang/Phi_medner-soap_chart_progressnotes_lora/resolve/main/training_args.bin
- Command line
-
hf download hf://emilykang/Phi_medner-soap_chart_progressnotes_lora/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/emilykang/Phi_medner-soap_chart_progressnotes_lora/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 0c6767923d355a560b74b8a856576f3bb047a6570afde16b7b60c15028e9faf5
- Size of remote file:
- 5.05 kB
- SHA256:
- 5f760f3ad93b9f9557c78e7dd945727a6ef5609bf892a0287eb7cdc9f357a31b
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