Instructions to use bane5631/b16d3ae9-0778-4227-8847-a52a0826b669 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bane5631/b16d3ae9-0778-4227-8847-a52a0826b669 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, "bane5631/b16d3ae9-0778-4227-8847-a52a0826b669") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a826deba4acb3009e1f594172dc4fb453a10b55777bf63435170195013c88e51
- Size of remote file:
- 84 MB
- SHA256:
- 76031683fe87a5aefde0d11992bc79cb93038833a20bd3297c585b4faf341c66
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