Instructions to use fats-fme/0da588f1-912c-4c29-813c-5f3bd769f3c0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use fats-fme/0da588f1-912c-4c29-813c-5f3bd769f3c0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "fats-fme/0da588f1-912c-4c29-813c-5f3bd769f3c0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee8a676e890d300140a26d67d7506bea352ebf9afe14c898755bb5078e6eef1a
- Size of remote file:
- 6.78 kB
- SHA256:
- 87e70e963bcb881a3e3a7968edfa395ab93ba44023e319b5c953234c93de663d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.