Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use lcaragiov/classifier-chapter4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lcaragiov/classifier-chapter4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lcaragiov/classifier-chapter4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lcaragiov/classifier-chapter4") model = AutoModelForSequenceClassification.from_pretrained("lcaragiov/classifier-chapter4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51fc8aaf113904df805ad28df2b1a3f0ff1c1526f3923b26cb834f19315f78f6
- Size of remote file:
- 5.78 kB
- SHA256:
- 13a4a2e7b049af6d2cd7ca5b2451d8fae4d0c2f0d452fc8fb908af8eaa35cb9d
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