PEFT
TensorBoard
Safetensors
gemma
alignment-handbook
trl
sft
Generated from Trainer
4-bit precision
bitsandbytes
Instructions to use chansung/coding_llamaduo_result2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use chansung/coding_llamaduo_result2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-7b") model = PeftModel.from_pretrained(base_model, "chansung/coding_llamaduo_result2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09ff396a80a326ec62c972b9fc6d530ae762221cf095d7f7f197c2b353cd8297
- Size of remote file:
- 5.11 kB
- SHA256:
- 7e9273a80e003a6ff95c501818ba7a2f106d6a6b04811879ecfb9a6d798d9dee
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.