Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use xshubhamx/distilbert-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xshubhamx/distilbert-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xshubhamx/distilbert-base-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xshubhamx/distilbert-base-cased") model = AutoModelForSequenceClassification.from_pretrained("xshubhamx/distilbert-base-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1fb8b2f3ee1c06795dbfe518ee966dd1a88bffe1a66e55ae9ebc6e1425c9a220
- Size of remote file:
- 4.92 kB
- SHA256:
- 356040a3afb7d54ef3650956d4142f5170f03ec6b31c34023d7e472253b34365
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