Instructions to use cpheemagazine/a0795576-991a-4eb6-ab3f-3f4e05602555 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cpheemagazine/a0795576-991a-4eb6-ab3f-3f4e05602555 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("samoline/59a2f6c0-e750-406f-bd9a-9f1c81bd29b1") model = PeftModel.from_pretrained(base_model, "cpheemagazine/a0795576-991a-4eb6-ab3f-3f4e05602555") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9aa0241fd9c3d26566e6b66a311d71caae4407c13f97b28cff24acb36bdf4890
- Size of remote file:
- 22.6 MB
- SHA256:
- b94ef8422737c10b105d36d0162c7de45e258a5f5e980b867086fe213b69e517
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