Instructions to use vmpsergio/f3e6c8e0-4f8c-4f37-9fb9-199f1a99090c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vmpsergio/f3e6c8e0-4f8c-4f37-9fb9-199f1a99090c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-135M") model = PeftModel.from_pretrained(base_model, "vmpsergio/f3e6c8e0-4f8c-4f37-9fb9-199f1a99090c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a78b620b4c5cd2a264de43b419b95650ba3376ab3ffc45025b24764794694960
- Size of remote file:
- 19.6 MB
- SHA256:
- 9063db456df82ef7b034a44b128b7b65ac821a1352a1dd757dfba2826368b8b7
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