Text Classification
Transformers
TensorFlow
xlm-roberta
generated_from_keras_callback
text-embeddings-inference
Instructions to use cruiser/roberta_tensorflow_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cruiser/roberta_tensorflow_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cruiser/roberta_tensorflow_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cruiser/roberta_tensorflow_test") model = AutoModelForSequenceClassification.from_pretrained("cruiser/roberta_tensorflow_test") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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README.md
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tags:
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- generated_from_keras_callback
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model-index:
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- name: cruiser/roberta_tensorflow_test
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results: []
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---
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tags:
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- generated_from_keras_callback
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base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment
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model-index:
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- name: cruiser/roberta_tensorflow_test
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results: []
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