Instructions to use dimasik2987/2fe4a68a-315c-45ae-9563-f3a6bccca3cd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik2987/2fe4a68a-315c-45ae-9563-f3a6bccca3cd 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, "dimasik2987/2fe4a68a-315c-45ae-9563-f3a6bccca3cd") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3bf4d0309541ff137ffc47bcaba70807a403e9a92ca9f78d9413338f51404504
- Size of remote file:
- 6.78 kB
- SHA256:
- 4259fc34258a43a6923c5d51afb42c8ac0822037f3bf942f7b39f914bf733ef1
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