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:
- 514136bb5e3f1937403cd9ad3839d667131f0abbe3ec48f73edea4750e18c652
- Size of remote file:
- 867 MB
- SHA256:
- e0fa6b93cd33ea24abaf4d96734fbe2e1677049155fc6d1732022dbb25e06806
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