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_14-03-46_a6a0c55f07b0 /events.out.tfevents.1717941827.a6a0c55f07b0.35.0
- Xet hash:
- 04a5d753b6847d1ba6e079ed30951b46896d58ec3414c4a06f6acec5f06f90cc
- Size of remote file:
- 7.62 kB
- SHA256:
- 2bba5605d10ae4f65d8f25fedd662825f08d9d76218d245a7c15dfa10db287a0
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