Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use isaacaderogba/tonality with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use isaacaderogba/tonality with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="isaacaderogba/tonality")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("isaacaderogba/tonality") model = AutoModelForSequenceClassification.from_pretrained("isaacaderogba/tonality", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7af74768e6e5b81a15a8031bda7a21bed9c25ce958bb782147bf54f2ea8f23b1
- Size of remote file:
- 399 MB
- SHA256:
- 09259c12c1c3db8fe26b605adfc2caa328081ee2854a7aab311112e80aa9eb04
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