Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use HarBat/distilled_bert_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HarBat/distilled_bert_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HarBat/distilled_bert_finetuning")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HarBat/distilled_bert_finetuning") model = AutoModelForSequenceClassification.from_pretrained("HarBat/distilled_bert_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- pytorch_model.bin +1 -1
- runs/Oct13_21-27-25_HarBat/1665714445.3398106/events.out.tfevents.1665714445.HarBat.19260.4 +3 -0
- runs/Oct13_21-27-25_HarBat/events.out.tfevents.1665714445.HarBat.19260.3 +3 -0
- runs/Oct13_21-27-25_HarBat/events.out.tfevents.1665714504.HarBat.19260.5 +3 -0
- training_args.bin +1 -1
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