Instructions to use dimasik87/1d112a59-f4ac-450e-b382-4095165f1529 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/1d112a59-f4ac-450e-b382-4095165f1529 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-2b-it") model = PeftModel.from_pretrained(base_model, "dimasik87/1d112a59-f4ac-450e-b382-4095165f1529") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from dimasik87/1d112a59-f4ac-450e-b382-4095165f1529: direct link, hf CLI and curl.
- Browser
- Download file 166 MB
-
https://huggingface.co/dimasik87/1d112a59-f4ac-450e-b382-4095165f1529/resolve/main/adapter_model.bin
- Command line
-
hf download hf://dimasik87/1d112a59-f4ac-450e-b382-4095165f1529/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/dimasik87/1d112a59-f4ac-450e-b382-4095165f1529/resolve/main/adapter_model.bin
166 MB
- Xet hash:
- 8aa1207348076bf6170a5e8866da13b85b882076bce62089c4721ce14b32151e
- Size of remote file:
- 166 MB
- SHA256:
- 10fa1440d1b54b47ba144dc86257b5abd578ab626760fc3bda1c3f315d3fe77a
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