Instructions to use Mardiyyah/no_vague_no_downsample with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mardiyyah/no_vague_no_downsample with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Mardiyyah/no_vague_no_downsample")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Mardiyyah/no_vague_no_downsample") model = AutoModelForTokenClassification.from_pretrained("Mardiyyah/no_vague_no_downsample") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 4.455445544554456, | |
| "eval_accuracy": 0.9815417166677193, | |
| "eval_f1": 0.7460203642621539, | |
| "eval_loss": 0.07425664365291595, | |
| "eval_precision": 0.712798026856673, | |
| "eval_recall": 0.7824909747292419, | |
| "eval_samples": 2614, | |
| "total_flos": 760697313381126.0, | |
| "train_loss": 0.1482748039563497, | |
| "train_runtime": 320.0844, | |
| "train_samples": 6453, | |
| "train_samples_per_second": 403.206, | |
| "train_steps_per_second": 12.622 | |
| } |