Instructions to use coder1969/gemma-2-2b-scientific-summarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use coder1969/gemma-2-2b-scientific-summarizer with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-2b") model = PeftModel.from_pretrained(base_model, "coder1969/gemma-2-2b-scientific-summarizer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f626014f493efc12051e33d2403b4adf85556497df99aa6a8f98dcb73e2b6b10
- Size of remote file:
- 34.4 MB
- SHA256:
- 487cee8724215dcd2dde8888539e8b1bf844ceb5dbbe27f7845abda69eeb060f
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