Instructions to use sahabajalam/Med_scribe_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sahabajalam/Med_scribe_V2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/medgemma-1.5-4b-it") model = PeftModel.from_pretrained(base_model, "sahabajalam/Med_scribe_V2") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sahabajalam/Med_scribe_V2: direct link, hf CLI and curl.
- Browser
- Download file 6.29 kB
-
https://huggingface.co/sahabajalam/Med_scribe_V2/resolve/main/training_args.bin
- Command line
-
hf download hf://sahabajalam/Med_scribe_V2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sahabajalam/Med_scribe_V2/resolve/main/training_args.bin
6.29 kB
- Xet hash:
- d92604d936f48567fa7f597507c577db9d4b5a5fb1fe231069eedaa5fed05a6f
- Size of remote file:
- 6.29 kB
- SHA256:
- 5cab99db08661657b0ac7809677925c5418ac629d953f53ee08ed8fa4b444652
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