Instructions to use nblinh63/4e6fe6b2-2f3a-4bac-9ccf-e39a9628f596 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nblinh63/4e6fe6b2-2f3a-4bac-9ccf-e39a9628f596 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-7b-it") model = PeftModel.from_pretrained(base_model, "nblinh63/4e6fe6b2-2f3a-4bac-9ccf-e39a9628f596") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 379aef98483c05bff823dc276ee03d789a6de813aee2e850d2336a0ec40c99b8
- Size of remote file:
- 200 MB
- SHA256:
- d4cfd2ae128ccdff17178f2249f195a2d3b22f252e3ea3f8e1a07ccc95be42df
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