Text Classification
Transformers
PyTorch
English
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use madmancity/bert2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use madmancity/bert2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="madmancity/bert2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("madmancity/bert2") model = AutoModelForSequenceClassification.from_pretrained("madmancity/bert2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08b6467b4451c91c5e5546aa8657fb66c3c25196545ded9defd42fe1529f395d
- Size of remote file:
- 712 kB
- SHA256:
- 41b9d12a4c559e4098f30173bc0f76d092c43d7b1f873e7027da45a256f30f87
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