Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use padmajabfrl/demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use padmajabfrl/demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="padmajabfrl/demo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("padmajabfrl/demo") model = AutoModelForSequenceClassification.from_pretrained("padmajabfrl/demo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe589c934dd5457ee66ed04f825fe1356ee7031934c2812f5d0deaca36c1620c
- Size of remote file:
- 3.39 kB
- SHA256:
- a307a396b7cf004e078e2e31d170300ed1410153fc0916bf42847f1e937ee7fc
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