Text Classification
Transformers
TensorBoard
Safetensors
English
deberta-v2
deberta-v3
text-embeddings-inference
Instructions to use sitenote/ticker-news-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sitenote/ticker-news-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sitenote/ticker-news-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sitenote/ticker-news-classifier") model = AutoModelForSequenceClassification.from_pretrained("sitenote/ticker-news-classifier") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse filesAdded model card.
README.md
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---
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license: apache-2.0
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datasets:
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- sitenote/ticker_news_classifier_2
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language:
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- en
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metrics:
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- f1
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base_model:
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- microsoft/deberta-v3-base
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tags:
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- transformers
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- text-classification
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- deberta-v3
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---
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