Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use hypo69/my_text_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hypo69/my_text_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hypo69/my_text_classification_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hypo69/my_text_classification_model") model = AutoModelForSequenceClassification.from_pretrained("hypo69/my_text_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e123360db81b8899f570b9dc6eb62e33af1f37ff0d7318c758ae963dfded9d49
- Size of remote file:
- 268 MB
- SHA256:
- b1cebc5a8934a102179653deb6c022afc577cb0b8f7f67f0694c4af88fa52e83
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