Sentence Similarity
Transformers
Safetensors
English
roberta
text-classification
code
text-embeddings-inference
Instructions to use UNSW990025T2Transformer/Header_Extraction_Robert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UNSW990025T2Transformer/Header_Extraction_Robert with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("UNSW990025T2Transformer/Header_Extraction_Robert") model = AutoModelForSequenceClassification.from_pretrained("UNSW990025T2Transformer/Header_Extraction_Robert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43ea67650caf09b438aaf79d25fb0a5b34ee294ae66d1975ba11c82600f5d1be
- Size of remote file:
- 499 MB
- SHA256:
- 0ace989a8a40f30694437f59a52e1d1ea4994dcc2e1e4a2c53a64ecb33c9b722
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