Instructions to use aleegis10/42e33b36-acc2-4cfe-9eba-d0e6fd6dcf29 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aleegis10/42e33b36-acc2-4cfe-9eba-d0e6fd6dcf29 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-llama-fast-tokenizer") model = PeftModel.from_pretrained(base_model, "aleegis10/42e33b36-acc2-4cfe-9eba-d0e6fd6dcf29") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e985a00c6bc43084e4606e29e917bec6c36f6d97270620cd15f3794781b2e0c5
- Size of remote file:
- 192 kB
- SHA256:
- 9d9b7c762bcacaf63f96096fa3dfb4b874f338771fcc9b486064e8a04f9def2a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.