Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use MarPla/BertAbstractComp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarPla/BertAbstractComp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MarPla/BertAbstractComp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MarPla/BertAbstractComp") model = AutoModelForSequenceClassification.from_pretrained("MarPla/BertAbstractComp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a02eac3331cd359fe746a29eacabaa1492f9836e1ba10c5db758f7a0ec826da
- Size of remote file:
- 438 MB
- SHA256:
- 8cd1e9ca9dbf1277d61ec73ab9f3af6b079e9479172241075fe14aef515466bb
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