Instructions to use A-Alsad/Falcon-7B-Instruct-SAT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use A-Alsad/Falcon-7B-Instruct-SAT with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("CleverShovel/falcon-7b-instruct-sharded-bf16") model = PeftModel.from_pretrained(base_model, "A-Alsad/Falcon-7B-Instruct-SAT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c6af0809d46fb250c287be174b7a9356a30f9417b5dfdd3533c5a1972146686
- Size of remote file:
- 522 MB
- SHA256:
- 55d19dbd6a655e929707747223cbc39d835eb85b3e52cbffc8d11f52306844e0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.