Text Classification
Transformers
PyTorch
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Theoreticallyhugo/bert-ner-essays-classify_span with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Theoreticallyhugo/bert-ner-essays-classify_span with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Theoreticallyhugo/bert-ner-essays-classify_span")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Theoreticallyhugo/bert-ner-essays-classify_span") model = AutoModelForSequenceClassification.from_pretrained("Theoreticallyhugo/bert-ner-essays-classify_span") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f8602c67c208a6cb871f9cce96800035769b1a34deaab7dc8c5ac91f3573508
- Size of remote file:
- 4.09 kB
- SHA256:
- 1d1c4c325e6044b22f2b8ec5c7d33679e868349933c538ad8a6466af08388fac
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