Text Classification
Transformers
Safetensors
code
roberta
feature-extraction
multi-task
structured-data
code-quality
content-type
regression
classification
starcoderdata
text-embeddings-inference
Instructions to use mdonigian/code-curator-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mdonigian/code-curator-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mdonigian/code-curator-v1")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("mdonigian/code-curator-v1") model = AutoModel.from_pretrained("mdonigian/code-curator-v1") - Notebooks
- Google Colab
- Kaggle
| epoch,train_loss,val_loss,val_quality_mae,val_quality_mse,val_quality_rounded_acc,val_quality_spearman,val_structured_data_mae,val_structured_data_mse,val_structured_data_rounded_acc,val_structured_data_spearman,val_content_type_accuracy,val_content_type_macro_f1,val_combined_mae | |
| 1,1.9338482332460847,1.448065088578718,0.6309319138526917,0.7191991209983826,0.522108666179998,0.553817859073393,0.45338281989097595,0.35454854369163513,0.6431848993638544,0.79499171167133,0.8623944102617582,0.6234108515025513,0.5421573668718338 | |
| 2,1.3254653735931108,1.3402525051073595,0.6033948659896851,0.6770005226135254,0.5472937741161747,0.5729696168341741,0.42503005266189575,0.32683703303337097,0.6662842840755032,0.8050313624661184,0.8754823234956721,0.6905006297568385,0.5142124593257904 | |
| 3,1.1299075901272126,1.3563477016171384,0.6024025678634644,0.6801310777664185,0.5458337678590051,0.5730787938638631,0.4216791093349457,0.33049410581588745,0.6724893106684743,0.8050240322085739,0.8755866096568985,0.6923274552582193,0.512040838599205 | |