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:
- 5bdfb8a37d973e24bfb34a9b26f2b40e8851c1faf3db52781e057a5530d15108
- Size of remote file:
- 41.6 MB
- SHA256:
- bd40bf6ce2d4cf1f2fdb1b84176e46b09e7f1538fb97583aff39328ac38e27b4
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