Instructions to use tarabukinivanhome/8e227918-5a73-4542-867a-e82bfd1a23d4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tarabukinivanhome/8e227918-5a73-4542-867a-e82bfd1a23d4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "tarabukinivanhome/8e227918-5a73-4542-867a-e82bfd1a23d4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5063c651a4c101a1eaeaa2198a80f8c0cc35336b2115f9e07d04b403ce4320c
- Size of remote file:
- 336 MB
- SHA256:
- 44964193991a02e25c2e35439021dc0b57f0c8db1c562f632ef246855c07ff8e
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