Instructions to use rayonlabs/af6dd40b-32e1-43b1-adfd-8ce14d65d738-PubMedQA-3a116654-3a74-492a-90ce-9f7fcbc82665 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rayonlabs/af6dd40b-32e1-43b1-adfd-8ce14d65d738-PubMedQA-3a116654-3a74-492a-90ce-9f7fcbc82665 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Henrychur/MMed-Llama-3-8B-EnIns") model = PeftModel.from_pretrained(base_model, "rayonlabs/af6dd40b-32e1-43b1-adfd-8ce14d65d738-PubMedQA-3a116654-3a74-492a-90ce-9f7fcbc82665") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 452eebd906bfa6da082de9ea135bcc344046183396a10391329d4e32c0e04d00
- Size of remote file:
- 671 MB
- SHA256:
- f8f2432208c5a03e162a8b3f6b4ee6b3e991eb62ea7b6e1e626edf58698615f4
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