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:
- f15d53154c1e34710b9063f581e85ab220e88d239b4dfb04793715bd87d529bb
- Size of remote file:
- 6.78 kB
- SHA256:
- f2f38358857a143249f0ef8ce033109a4aab15c421a3918f9d7a43a68cc1c41f
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