Instructions to use nhunglaaaaaaa/ae4ae03b-18cf-4396-91ee-4dd68771f155 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhunglaaaaaaa/ae4ae03b-18cf-4396-91ee-4dd68771f155 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Vikhrmodels/Vikhr-7B-instruct_0.4") model = PeftModel.from_pretrained(base_model, "nhunglaaaaaaa/ae4ae03b-18cf-4396-91ee-4dd68771f155") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bd902e2004186a2bb02d7c6261a2f974e739b479e60b0a7cc840bc4b29b6aa5
- Size of remote file:
- 6.78 kB
- SHA256:
- bebe69ba2c53e0ec6c61b9609a8c74175b6731153cdf3d77583eec2c387bd5c0
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