Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Mathildeholst/classifier-chapter4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mathildeholst/classifier-chapter4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mathildeholst/classifier-chapter4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mathildeholst/classifier-chapter4") model = AutoModelForSequenceClassification.from_pretrained("Mathildeholst/classifier-chapter4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3f4cf8c7d272da0f33fece2fd65c9bef60849fd28334727218d5f7b105283c6
- Size of remote file:
- 268 MB
- SHA256:
- 5ee975f3794c2af94df5627b18087e63b8013d5884a20808531c6bae29de97d2
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