PEFT
TensorBoard
Safetensors
gemma
alignment-handbook
trl
sft
Generated from Trainer
4-bit precision
bitsandbytes
Instructions to use chansung/coding_llamaduo_result3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use chansung/coding_llamaduo_result3 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_result3") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 10.0, | |
| "eval_loss": 1.750213384628296, | |
| "eval_runtime": 1.1155, | |
| "eval_samples": 16, | |
| "eval_samples_per_second": 1.793, | |
| "eval_steps_per_second": 0.896, | |
| "total_flos": 1.257706785410646e+18, | |
| "train_loss": 1.5742560074096772, | |
| "train_runtime": 5911.531, | |
| "train_samples": 19039, | |
| "train_samples_per_second": 2.214, | |
| "train_steps_per_second": 0.139 | |
| } |