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:
- 7eebba01ab471a7806e3bf3b73d3e1b1bf5e61d29a83a18435f5ead69877bea0
- Size of remote file:
- 7.22 kB
- SHA256:
- e4d3164a8714cbdb7412263747d0ee6f39b66d3175e24991e417f7e3d01dae5f
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