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:
- 7cc6a38ea65f6ea7ea240f215d35686d75c77e62176d8e39532cbd3d542696ad
- Size of remote file:
- 5.11 kB
- SHA256:
- baa96576a7ed0fa72375d0bfdbab65eff4b6d8b361af689a7151e16e4975173d
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