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:
- a50a031de8e7534e62b79bd7b950210a0f95f0afed61682d849efd648fda6e58
- Size of remote file:
- 499 MB
- SHA256:
- f2820243cd148d8d2c68af7eb396150bd7dada213ff227cb2723dd3b7463c7c5
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