Instructions to use hsaglamlar/stress_twitter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hsaglamlar/stress_twitter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hsaglamlar/stress_twitter")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hsaglamlar/stress_twitter") model = AutoModelForSequenceClassification.from_pretrained("hsaglamlar/stress_twitter") - Notebooks
- Google Colab
- Kaggle
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README.md
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tags: autotrain
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language: en
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widget:
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- text: "I love AutoTrain 🤗"
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## Usage
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You can use cURL to access this model:
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---
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language: en
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widget:
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- text: "I love AutoTrain 🤗"
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- F1: 0.7507331378299119
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## Usage
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This model finds self-reported stress from txt.
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You can use cURL to access this model:
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