Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use BruceT02/DistilBert_Exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BruceT02/DistilBert_Exp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BruceT02/DistilBert_Exp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BruceT02/DistilBert_Exp") model = AutoModelForSequenceClassification.from_pretrained("BruceT02/DistilBert_Exp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e4a532a569c0bbf42377af7899e1c1c2febb7528e1b26bee401034d698b6361
- Size of remote file:
- 268 MB
- SHA256:
- e72168fda46c9bc83d40a9818f4035ec095532663936e5f8287d20ceb0b7c3ef
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