Text Classification
Transformers
Safetensors
English
bert
spam
ham
email
tinybert
enron
Eval Results (legacy)
text-embeddings-inference
Instructions to use prancyFox/tiny-bert-enron-spam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prancyFox/tiny-bert-enron-spam with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="prancyFox/tiny-bert-enron-spam")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("prancyFox/tiny-bert-enron-spam") model = AutoModelForSequenceClassification.from_pretrained("prancyFox/tiny-bert-enron-spam", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9c3e97f0ecd18efa2dd854e1e0856f4943a37882a74c73d6e71fd2eec5f0b7c
- Size of remote file:
- 14.5 kB
- SHA256:
- 1de2b097645ef63b5f39b7d0900a00d6c8ec01b95c6c8ecf10c3ca73b9e23367
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.