Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use RayenLLM/bert-practice-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RayenLLM/bert-practice-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RayenLLM/bert-practice-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RayenLLM/bert-practice-classifier") model = AutoModelForSequenceClassification.from_pretrained("RayenLLM/bert-practice-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1759dfee3af970bad9a874f4136f7ae8b670d1b50ffff1d0aa7f7bf486678314
- Size of remote file:
- 5.37 kB
- SHA256:
- 27153ef153cd5fb9313dccf6dba6eb925400e20bef3bcd5f04e12b0d5d594a58
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