Instructions to use dejanai/sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dejanai/sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dejanai/sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dejanai/sentiment") model = AutoModelForSequenceClassification.from_pretrained("dejanai/sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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This is a demo model which may occassionally misclasify some texts. In a typical commercial project, a larger model is deployed for the task, and in special cases, a domain-specific model is developed for the client.
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# Engage Our Team
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Interested in using this in an automated pipeline for bulk
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Please [book an appointment](https://dejanmarketing.com/conference/) to discuss your needs.
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This is a demo model which may occassionally misclasify some texts. In a typical commercial project, a larger model is deployed for the task, and in special cases, a domain-specific model is developed for the client.
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# Engage Our Team
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Interested in using this in an automated pipeline for bulk URL and text processing?
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Please [book an appointment](https://dejanmarketing.com/conference/) to discuss your needs.
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