Instructions to use emilykang/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/medner-soap_chart_progressnotes_lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0") model = PeftModel.from_pretrained(base_model, "emilykang/medner-soap_chart_progressnotes_lora") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from emilykang/medner-soap_chart_progressnotes_lora: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/emilykang/medner-soap_chart_progressnotes_lora/resolve/main/training_args.bin
- Command line
-
hf download hf://emilykang/medner-soap_chart_progressnotes_lora/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/emilykang/medner-soap_chart_progressnotes_lora/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 82f1d5757c14e4f0b60daf92d6e0cdfb96f1ba65e17d7869defda1be554f834b
- Size of remote file:
- 5.05 kB
- SHA256:
- f5fe5079a2acc69aaf18609dc0cf0b246c6a2eb2d707b5f5cd6617d186da90be
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