Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use xshubhamx/bert-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xshubhamx/bert-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xshubhamx/bert-base-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xshubhamx/bert-base-cased") model = AutoModelForSequenceClassification.from_pretrained("xshubhamx/bert-base-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b3b3f62fcb535bba10165bc0def5d3d7b0f4fdfe652e814cf62192a43b61137
- Size of remote file:
- 867 MB
- SHA256:
- 455d9d3dad6ac9427ecd67e27600433fe5115108cd405c2dc9a9a1e1471ee2ff
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