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
| { | |
| "epoch": 1.0, | |
| "eval_loss": 1.1440011262893677, | |
| "eval_runtime": 1218.8914, | |
| "eval_samples": 23110, | |
| "eval_samples_per_second": 13.263, | |
| "eval_steps_per_second": 13.263 | |
| } |