Instructions to use thaffggg/a4c6e736-e9a9-45a7-8568-0843fbfe65d2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thaffggg/a4c6e736-e9a9-45a7-8568-0843fbfe65d2 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, "thaffggg/a4c6e736-e9a9-45a7-8568-0843fbfe65d2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c6006305023e1e61dec883043a1718851b20a30a4885e066c3108ce0eeea685
- Size of remote file:
- 6.78 kB
- SHA256:
- 56864765cb04060a20edc356d147cb0e07fb213b05f79d0f599e399c3e74aee5
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