Instructions to use dzanbek/19c416b4-148d-48ab-9712-2e39930df74a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/19c416b4-148d-48ab-9712-2e39930df74a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Theta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "dzanbek/19c416b4-148d-48ab-9712-2e39930df74a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53330a982236ffbf9aa00baefcdd7d2278870ab6d2c2eabea9f007a7a1c27ea1
- Size of remote file:
- 2.27 GB
- SHA256:
- f3636753596d3e9e57fa9f363ea7e09385ef7242d1dea631f73c72ff376de002
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