Text Classification
Transformers
TensorBoard
Safetensors
English
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Hartunka/bert_base_km_20_v1_mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hartunka/bert_base_km_20_v1_mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hartunka/bert_base_km_20_v1_mrpc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hartunka/bert_base_km_20_v1_mrpc") model = AutoModelForSequenceClassification.from_pretrained("Hartunka/bert_base_km_20_v1_mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
End of training
Verified signature3770b8b -
Model save
Verified signaturef473050 -
Training in progress, epoch 5
Verified signature04ff6cf -
Training in progress, epoch 4
Verified signaturea0161b2 -
Training in progress, epoch 1
Verified signature14a5ed6 -
End of training
Verified signatureec6555f -
Model save
Verified signaturebbd7668 -
Training in progress, epoch 4
Verified signature06182cf -
Training in progress, epoch 1
Verified signature865fdde -
initial commit
Verified signaturea9d385e