Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use Defensa2025/C2BERT4060 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Defensa2025/C2BERT4060 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Defensa2025/C2BERT4060")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Defensa2025/C2BERT4060") model = AutoModelForSequenceClassification.from_pretrained("Defensa2025/C2BERT4060", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51addf91602a9141bfd7b9c5fedc5aa9c5dc3eff2aa03cdb936fdd09fd5929a6
- Size of remote file:
- 5.37 kB
- SHA256:
- d48138acbe2655fbef6c3e61c5ab5c5eeaabd1841ea312970aa64746023bf220
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