Text Classification
Transformers
TensorFlow
English
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use tchebonenko/As1b-distilbert_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tchebonenko/As1b-distilbert_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tchebonenko/As1b-distilbert_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tchebonenko/As1b-distilbert_classifier") model = AutoModelForSequenceClassification.from_pretrained("tchebonenko/As1b-distilbert_classifier") - Notebooks
- Google Colab
- Kaggle
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README.md
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the 20 newsgroups dataset.
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The [details](https://scikit-learn.org/stable/datasets/real_world.html#newsgroups-dataset) about the dataset from Scikit Learn.
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It achieves the following results on the evaluation set:
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## Training procedure
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the 20 newsgroups dataset.
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The [details](https://scikit-learn.org/stable/datasets/real_world.html#newsgroups-dataset) about the dataset from Scikit Learn.
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## Training procedure
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