Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use W4nkel/distilbertBase128KTrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use W4nkel/distilbertBase128KTrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="W4nkel/distilbertBase128KTrain")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("W4nkel/distilbertBase128KTrain") model = AutoModelForSequenceClassification.from_pretrained("W4nkel/distilbertBase128KTrain") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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by librarian-bot - opened
README.md
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license: mit
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tags:
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- generated_from_keras_callback
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model-index:
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- name: W4nkel/distilbertBase128KTrain
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results: []
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license: mit
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tags:
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- generated_from_keras_callback
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base_model: dbmdz/distilbert-base-turkish-cased
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model-index:
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- name: W4nkel/distilbertBase128KTrain
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results: []
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