Instructions to use johngreendr1/434751be-3cfc-4ac1-a368-efb18b4b6501 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use johngreendr1/434751be-3cfc-4ac1-a368-efb18b4b6501 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, "johngreendr1/434751be-3cfc-4ac1-a368-efb18b4b6501") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73e27d7b298a04bd1b2378eb61599ec6481b703f594bd0942c7e3f004749fe52
- Size of remote file:
- 1.64 MB
- SHA256:
- e3f0f84b42f79947ab92931c7c5ded699e845e6862e4e29f0b97f87e279da601
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