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_15-13-40_a6a0c55f07b0 /events.out.tfevents.1717946020.a6a0c55f07b0.35.2
- Xet hash:
- e43df5b690ac0cbb79048a49d5e17a6bfed7fd2276c9b42dd53975f70d83cc41
- Size of remote file:
- 7.71 kB
- SHA256:
- c4ce94f8949b8b237d6087df150254030ab30f723d5d45bcc4bf19ebb1a77686
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