Instructions to use luckjsg/fbc9aeb3-7113-4701-9ac2-fa460b20cfcb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use luckjsg/fbc9aeb3-7113-4701-9ac2-fa460b20cfcb 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, "luckjsg/fbc9aeb3-7113-4701-9ac2-fa460b20cfcb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37b750b834e55b189e0d649de651353ed3f109dbca7e5f78c0b432792e88817a
- Size of remote file:
- 1.34 GB
- SHA256:
- cf78b8cefa57fe07fa74a816743d6971731fbf7979e3377ab82756c030a2067c
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