Instructions to use mskov/falcon-7b-completion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mskov/falcon-7b-completion with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("ybelkada/falcon-7b-sharded-bf16") model = PeftModel.from_pretrained(base_model, "mskov/falcon-7b-completion") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ccd4f5acd48668d6a8d610f2e4c88c8cbafcd3c1c1122bc59a97443e37fab66
- Size of remote file:
- 8.51 GB
- SHA256:
- b2482295e16817bc0f1ef361ecf594201247f8893a472a2ea5326a5f3892ff68
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.