PEFT
TensorBoard
Safetensors
llama
alignment-handbook
Generated from Trainer
trl
sft
4-bit precision
bitsandbytes
Instructions to use dball/zephyr-tiny-sft-qlora-quantized-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dball/zephyr-tiny-sft-qlora-quantized-2 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, "dball/zephyr-tiny-sft-qlora-quantized-2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79158e23123933f3a10db55f4383a35b6ffd4afa88010a04d54806e38348b51c
- Size of remote file:
- 4.79 kB
- SHA256:
- 216509f65e6fd3ab9c953590c2c9ee230731220b2c871058797b8e3eabe908ea
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.