Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use classicakeza5/exp_number0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use classicakeza5/exp_number0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="classicakeza5/exp_number0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("classicakeza5/exp_number0") model = AutoModelForSequenceClassification.from_pretrained("classicakeza5/exp_number0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b185ab1266a9607d2007750af89155ba9be4361811eda11e7a8cd239dc1e903a
- Size of remote file:
- 4.92 kB
- SHA256:
- 9337228af7586ce7808a19f7b8fb92206bfe75d6b63e7c9c5a145b394414a38e
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