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:
- 7f4e88662841ebac9060c2c52293db8d0f4fb66c9dd67e618a20aa56d489f207
- Size of remote file:
- 42 MB
- SHA256:
- 385a5fb32b93dfa0066750595a4e1768fa4f565efc59fe182985d20827b81b28
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