Instructions to use wnkh/IOC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wnkh/IOC with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("wnkh/IOC") model = AutoModelForSeq2SeqLM.from_pretrained("wnkh/IOC") - Notebooks
- Google Colab
- Kaggle
File size: 543 Bytes
9d21e6c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"model_name": "google/byt5-small",
"dataset_name": "wnkh/medieval-latin-ocr-correction",
"train_samples": 90163,
"val_samples": 4746,
"training_time_hours": 3.8745588700638876,
"final_train_loss": 0.4137230705283639,
"final_eval_results": {
"eval_loss": 0.36988574266433716,
"eval_cer": 0.1665792765941789,
"eval_cer_raw": 0.18652676107827693,
"eval_exact_match": 0.1571849978929625,
"eval_runtime": 1012.6473,
"eval_samples_per_second": 4.687,
"eval_steps_per_second": 1.172,
"epoch": 7.0
}
} |