Instructions to use nblinh63/56151d9e-4d31-478c-ae4c-50c1fab59312 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nblinh63/56151d9e-4d31-478c-ae4c-50c1fab59312 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-135M") model = PeftModel.from_pretrained(base_model, "nblinh63/56151d9e-4d31-478c-ae4c-50c1fab59312") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30f801b4176714d0ac7a3dd06078ff72d7af36feac2cd728605e75d84f8af644
- Size of remote file:
- 6.78 kB
- SHA256:
- a15b649f9df8b64f5b53d2d53f01285cbbf1c8b9f806a7cb1b98607278b076f5
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