Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use OliverHeine/distilbert-base-uncased_fold_9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/distilbert-base-uncased_fold_9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/distilbert-base-uncased_fold_9")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/distilbert-base-uncased_fold_9") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/distilbert-base-uncased_fold_9") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4233a78ac61a8a433f58fff8eea68de6b45a49f740fa74a6de0ccfa2981b8637
- Size of remote file:
- 5.33 kB
- SHA256:
- e96961b5c27b86aecd4b2bfa745e895bbe19b431d34b3bc69c01ad1283adf8b0
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