Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use OliverHeine/distilbert-base-uncased_fold_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/distilbert-base-uncased_fold_0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/distilbert-base-uncased_fold_0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/distilbert-base-uncased_fold_0") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/distilbert-base-uncased_fold_0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c25ac9640e3e23e511f667abca7fa2c2b5d16dc280174609496b856736aca382
- Size of remote file:
- 5.33 kB
- SHA256:
- 0232fbe4307a9a550e7296cb5bffdd2729c60e8c1526a24ba5e694fc8e5fbf74
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