Text Classification
Transformers
TensorFlow
bert
generated_from_keras_callback
text-embeddings-inference
Instructions to use runningsnake/bert-base-sequence-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use runningsnake/bert-base-sequence-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="runningsnake/bert-base-sequence-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("runningsnake/bert-base-sequence-classification") model = AutoModelForSequenceClassification.from_pretrained("runningsnake/bert-base-sequence-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 507b8cb
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README.md
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## Training and evaluation data
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- TensorFlow 2.12.0
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- Datasets 2.14.0
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- Tokenizers 0.13.3
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## How to use
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## Limitations and bias
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## Training and evaluation data
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- TensorFlow 2.12.0
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- Datasets 2.14.0
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- Tokenizers 0.13.3
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## Evaluation results
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More information needed
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