Sentence Similarity
Transformers
Safetensors
English
bert
text-classification
code
text-embeddings-inference
Instructions to use UNSW990025T2Transformer/Header_Extraction_MiniLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UNSW990025T2Transformer/Header_Extraction_MiniLM with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("UNSW990025T2Transformer/Header_Extraction_MiniLM") model = AutoModelForSequenceClassification.from_pretrained("UNSW990025T2Transformer/Header_Extraction_MiniLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 893e83986c3d31276961f120680da466eec310c82523dd17cfcc5ecd93d43930
- Size of remote file:
- 133 MB
- SHA256:
- e89bde871521c691040b3446a66a0b651a95816fcab88a03dd287bd3d33d9073
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