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
BertAbstractComp / runs /Jun09_11-45-09_f1e1a3a8fe84 /events.out.tfevents.1717933510.f1e1a3a8fe84.34.1
- Xet hash:
- e06b1b1de50d1f36667ed5a3dc2dee84e359317a32c076298caa956255e45499
- Size of remote file:
- 9.87 kB
- SHA256:
- 2a6fb7fcdeb52ef97a67429c62947cb7506c07d40da60462ff95a364f088953c
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