Instructions to use dvilasuero/phi2-lora-quantized-distilabel-intel-orca-dpo-pairs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dvilasuero/phi2-lora-quantized-distilabel-intel-orca-dpo-pairs with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2") model = PeftModel.from_pretrained(base_model, "dvilasuero/phi2-lora-quantized-distilabel-intel-orca-dpo-pairs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3456e801b2012e0f015eaa2bb06f0d59e1bc5336627ec65f0dbf5b1597e5af1
- Size of remote file:
- 4.73 kB
- SHA256:
- 5586322c02c4f0a3f45e5b2bd3a585bc13803034df78f01694be297ffb2371a6
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