Instructions to use chauhoang/4675ba61-9ca2-498e-8468-0d072a10e981 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use chauhoang/4675ba61-9ca2-498e-8468-0d072a10e981 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/codegemma-2b") model = PeftModel.from_pretrained(base_model, "chauhoang/4675ba61-9ca2-498e-8468-0d072a10e981") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20be08cec207f1ef085b05fc8ee3c3188bf90a6164b58623b8b45e183a99f12a
- Size of remote file:
- 6.78 kB
- SHA256:
- 8b1596307dfbc0f8ee9ccbf21da1490c3179d54cf2cfd6fdf06c937630b1adda
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