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:
- 80cc8ae3b3ab9e03e05d702d901658d4154be3e96ed84a275af588f6ea02fc23
- Size of remote file:
- 168 MB
- SHA256:
- da074ac4d0c9af91d8a005377ccdaefd1964a480f2bca4fe1528e2c553882eaf
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