Instructions to use davidho27941/results_new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use davidho27941/results_new with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("yentinglin/Taiwan-LLM-7B-v2.1-chat") model = PeftModel.from_pretrained(base_model, "davidho27941/results_new") - Notebooks
- Google Colab
- Kaggle
results_new
This model is a fine-tuned version of yentinglin/Taiwan-LLM-7B-v2.1-chat 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 20
Training results
Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Downloads last month
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Base model
yentinglin/Taiwan-LLM-7B-v2.1-chat