Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use OliverHeine/distilbert-base-uncased_train_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/distilbert-base-uncased_train_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/distilbert-base-uncased_train_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/distilbert-base-uncased_train_v2") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/distilbert-base-uncased_train_v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7e7f993ec350b8241c8248867faa21885584ebd6698bb582ccd5114a800b7dc
- Size of remote file:
- 5.33 kB
- SHA256:
- 223436183c227a0335ae7748cf32d2a504ce5fed5419000fc292d1c777e13ba4
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