Instructions to use mamung/5c36bf90-833a-4aa9-996b-95dea707aa90 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mamung/5c36bf90-833a-4aa9-996b-95dea707aa90 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "mamung/5c36bf90-833a-4aa9-996b-95dea707aa90") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9511814ae522d9119f2ac8e1a4675696877645e8229ec181c3ff14e7f987402
- Size of remote file:
- 1.06 kB
- SHA256:
- 3a60c7d771c1fd156acee762fba03c724cb41829a3f71df370ecd1d20b134982
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