Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Izarel/distilbert-base-uncased_fine_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Izarel/distilbert-base-uncased_fine_tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Izarel/distilbert-base-uncased_fine_tuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Izarel/distilbert-base-uncased_fine_tuned") model = AutoModelForSequenceClassification.from_pretrained("Izarel/distilbert-base-uncased_fine_tuned") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 786dd346d67fb2681070107633e36b6520b4f5fc50efca78ebf87f4d865dbfd2
- Size of remote file:
- 3.31 kB
- SHA256:
- 19566cc0858339acbc9414301d2405f23dd61e79459017be98e79e331076fa5e
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