Instructions to use eeeebbb2/f1870551-e865-4496-82eb-3122c4c5fe07 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/f1870551-e865-4496-82eb-3122c4c5fe07 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/f1870551-e865-4496-82eb-3122c4c5fe07") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- deac7be11523fce72f8eb4dc4d20d14be0ca6ec7804f0a1d5fd5de5d3bb1b0e5
- Size of remote file:
- 400 MB
- SHA256:
- d331c7e6030766e769f887704aa79eac134180efed5d613180c11d567a115240
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