Instructions to use LorenzoMascia/tinyllama-lora-anonymizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use LorenzoMascia/tinyllama-lora-anonymizer with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0") model = PeftModel.from_pretrained(base_model, "LorenzoMascia/tinyllama-lora-anonymizer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 343d616167d29116f7620d2487a02f53f00b4f24e4e1c84167765feef8c92b4e
- Size of remote file:
- 5.37 kB
- SHA256:
- 3379c04a2779c7c5cd1bbbeb063fe34d48391d64314d5a3105e0fe15d00670f6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.