Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use JTH/twitter_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JTH/twitter_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JTH/twitter_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JTH/twitter_classification") model = AutoModelForSequenceClassification.from_pretrained("JTH/twitter_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28a51738a27b193528fa69c416f95a50ea2c329d75addbb56c53165f6a8fb202
- Size of remote file:
- 3.31 kB
- SHA256:
- 08b80342f455241806ad70dcd1bc788307634d30d371a31aea53d5f2448a4249
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