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:
- 4860ed7e33503c533764a944cfcd6043673698819b5c3c1827bc10e873ef3288
- Size of remote file:
- 4.92 kB
- SHA256:
- 0894bd98951986b8e704718873ae5f5449d3af1774205a3e5c6b8b3374fec4f2
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