Instructions to use aleegis10/328c7fca-9a6b-4269-9dfe-e170212caa1c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aleegis10/328c7fca-9a6b-4269-9dfe-e170212caa1c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-135M") model = PeftModel.from_pretrained(base_model, "aleegis10/328c7fca-9a6b-4269-9dfe-e170212caa1c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f1020c688faa78c20957e52c5e99873ca3f7294b041c445eb34dacd1a0398c0
- Size of remote file:
- 40.2 MB
- SHA256:
- 4b56e2103eb728a4b8a9543b05b230a1b1907a6ffcf8e5dc21a6bf156e54a1af
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