Text Classification
Transformers
TensorBoard
Safetensors
English
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use ubffm/academic_text_classifier_en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ubffm/academic_text_classifier_en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ubffm/academic_text_classifier_en")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ubffm/academic_text_classifier_en") model = AutoModelForSequenceClassification.from_pretrained("ubffm/academic_text_classifier_en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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associated with the grammar G4 as its value (with, let us
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## Training and evaluation data
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More information needed
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associated with the grammar G4 as its value (with, let us
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say, lower value indicated by higher number)
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Another type of input is, longer and sentence-like running titles. For example:
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- Verb Placement in Early West-Germanic 155
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## Training and evaluation data
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More information needed
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