Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use ThomasLI/roberta-base-finetuned-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThomasLI/roberta-base-finetuned-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ThomasLI/roberta-base-finetuned-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ThomasLI/roberta-base-finetuned-classification") model = AutoModelForSequenceClassification.from_pretrained("ThomasLI/roberta-base-finetuned-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 3
Browse files
pytorch_model.bin
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runs/Mar02_14-06-44_e672abcf8e77/events.out.tfevents.1677766023.e672abcf8e77.1027.0
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