Instructions to use abaddon182/4211dd7b-7323-4f98-88a0-2c950d914fad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use abaddon182/4211dd7b-7323-4f98-88a0-2c950d914fad 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, "abaddon182/4211dd7b-7323-4f98-88a0-2c950d914fad") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1cc6205f95c94614257f83e1a1d9e662e9de6f31f5b4e27642af11d1264b334c
- Size of remote file:
- 42 MB
- SHA256:
- 150be46ad6090c4b152a8deafe131adfa39d5aeda1c90a1baca7aaa0aaef3596
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