Instructions to use Serega6678/tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Serega6678/tmp with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "Serega6678/tmp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bda20f6be443b1449be1c00bf43e0ac720ef3117a80993400c870b7d579247bf
- Size of remote file:
- 4.79 kB
- SHA256:
- 625e24da9ccb9aabc6f68ca9c127cb0d58ea844c14e98bf605e748cc9d6b1bd3
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