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:
- 84d06af9d8894a5136dc2df29cdc310dc64aba164bce94b3819cfc092a59e3a1
- Size of remote file:
- 268 MB
- SHA256:
- 6c24afbd14d800508ffeba0e879058592bc80be0249c49f78f7029ba5efb14ed
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