Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use zwellington/bert-azahead-v1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zwellington/bert-azahead-v1.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zwellington/bert-azahead-v1.1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zwellington/bert-azahead-v1.1") model = AutoModelForSequenceClassification.from_pretrained("zwellington/bert-azahead-v1.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45cdaf97949b05ed273c6187140bd0384b54537f42989dc69d70ec76169f3e9a
- Size of remote file:
- 4.41 kB
- SHA256:
- 8569c0fad82a60ab2cf875b97ef57e23b26b21b6fce2cfeab806ce42ba7a58b8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.