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:
- f01428ab5927d54cc48f439b329b376ce2cb9c9317578ed37a668dc9feff9860
- Size of remote file:
- 17.2 MB
- SHA256:
- 18656043d3999331a98e43a10816aeee61f32f08d040685e527032cee016a1aa
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