Instructions to use uine/single-practice-fine-tuning-eeve-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use uine/single-practice-fine-tuning-eeve-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("yanolja/EEVE-Korean-Instruct-10.8B-v1.0") model = PeftModel.from_pretrained(base_model, "uine/single-practice-fine-tuning-eeve-adapter") - Notebooks
- Google Colab
- Kaggle
single-practice-fine-tuning-eeve
This model is a fine-tuned version of yanolja/EEVE-Korean-Instruct-10.8B-v1.0 on an unknown dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.19.0
- Tokenizers 0.15.2
- Downloads last month
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Model tree for uine/single-practice-fine-tuning-eeve-adapter
Base model
upstage/SOLAR-10.7B-v1.0 Finetuned
yanolja/YanoljaNEXT-EEVE-10.8B Finetuned
yanolja/YanoljaNEXT-EEVE-Instruct-10.8B