Instructions to use eeeebbb2/c2ea0498-877c-4acc-afee-824cd273b65b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/c2ea0498-877c-4acc-afee-824cd273b65b 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, "eeeebbb2/c2ea0498-877c-4acc-afee-824cd273b65b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65f562283c8ea413d6ea149a9941bc8d0a103b506b4d197a5d98b2409467fd47
- Size of remote file:
- 6.84 kB
- SHA256:
- 8aee8ed0984ef631dbe473294be979b3a7e3d422ec822090b6936f6160e091c3
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