Instructions to use aseratus1/d4486cca-2420-4b94-8cbe-dac9684699cf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aseratus1/d4486cca-2420-4b94-8cbe-dac9684699cf with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("teknium/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "aseratus1/d4486cca-2420-4b94-8cbe-dac9684699cf") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bcb956f08c2ee1b6cea34e914546521eaa30b20032031bd994a68ed54becb36
- Size of remote file:
- 84 MB
- SHA256:
- 0d982e2974d23d2c6c4b688f77c091ee2120548c31cde87b4e8ce8a1b979c669
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