Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use dsmsb/tweet-classification-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dsmsb/tweet-classification-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dsmsb/tweet-classification-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dsmsb/tweet-classification-v1") model = AutoModelForSequenceClassification.from_pretrained("dsmsb/tweet-classification-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d07938d63795032d15c419d3365d32d06ad59d69e36ca98ab1894e9cf2a99a3
- Size of remote file:
- 712 MB
- SHA256:
- 7f35c648a0e9e153cf7e22f4f48b86111e475e3f9e535654c71f8ffcc67f7359
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