Instructions to use dimasik87/5684b6f3-c695-47ce-9c22-0948a16cdf07 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/5684b6f3-c695-47ce-9c22-0948a16cdf07 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Nous-Hermes-2-Mistral-7B-DPO") model = PeftModel.from_pretrained(base_model, "dimasik87/5684b6f3-c695-47ce-9c22-0948a16cdf07") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70c3f5bdf18f04fe9bdef0e75e4b19b5e1a64684c70e187093f500d3de60f952
- Size of remote file:
- 6.84 kB
- SHA256:
- 97acff1e9982ed1a9254b837039a6aa7a87b932aaaf7da8dc36864f811e78767
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