Text Classification
Transformers
TensorFlow
roberta
generated_from_keras_callback
text-embeddings-inference
Instructions to use Zarkit/classificationEsp1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zarkit/classificationEsp1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Zarkit/classificationEsp1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Zarkit/classificationEsp1") model = AutoModelForSequenceClassification.from_pretrained("Zarkit/classificationEsp1") - 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: apache-2.0
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tags:
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- generated_from_keras_callback
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model-index:
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- name: classificationEsp1
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results: []
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license: apache-2.0
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tags:
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- generated_from_keras_callback
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base_model: PlanTL-GOB-ES/roberta-base-bne
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model-index:
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- name: classificationEsp1
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results: []
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