Text Generation
PEFT
Safetensors
medical
healthcare
maternal-health
sexual-health
reproductive-health
multilingual
african-languages
akan
amharic
luganda
swahili
lora
medgemma
conversational
Instructions to use KYAGABA/testmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use KYAGABA/testmodel with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/medgemma-27b-text-it") model = PeftModel.from_pretrained(base_model, "KYAGABA/testmodel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4c7aa84fb94a696d78f2bde62590a25b6741b7365ed842f9310b5dcab71d95d
- Size of remote file:
- 33.4 MB
- SHA256:
- 4667f2089529e8e7657cfb6d1c19910ae71ff5f28aa7ab2ff2763330affad795
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