Instructions to use sciedoc/neurojenml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sciedoc/neurojenml with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/medgemma-4b-it-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "sciedoc/neurojenml") - Notebooks
- Google Colab
- Kaggle
NeuroJenML SFT LoRA Adapter
This is the LoRA adapter fine-tuned on MedGemma-4B-it. Designed to predict central pathology from peripheral Alzheimer's findings.
Training Details
- Base Model:
google/medgemma-4b-it - Training Loss:
0.0878 - Training Epochs:
3 - Training Examples:
1747 - Validation Loss:
0.059457048773765564 - Adapter Configuration: LoRA (r=16, alpha=16)
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