Text Classification
Transformers
TensorFlow
English
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use ZachBeesley/toxic-comments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZachBeesley/toxic-comments with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ZachBeesley/toxic-comments")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ZachBeesley/toxic-comments") model = AutoModelForSequenceClassification.from_pretrained("ZachBeesley/toxic-comments") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): f4308fb
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README.md
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- name: ZachBeesley/toxic-comments
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results: []
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widget:
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- text:
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You are so ugly
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example_title: Toxic Example
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- text:
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I love you
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example_title: Non-Toxic Example
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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- Transformers 4.31.0
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- TensorFlow 2.12.0
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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- name: ZachBeesley/toxic-comments
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results: []
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widget:
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- text: You are so ugly
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example_title: Toxic Example
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- text: I love you
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example_title: Non-Toxic Example
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language:
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- en
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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- Transformers 4.31.0
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- TensorFlow 2.12.0
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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