Instructions to use U4RASD/ArGTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use U4RASD/ArGTC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="U4RASD/ArGTC")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("U4RASD/ArGTC") model = AutoModelForSequenceClassification.from_pretrained("U4RASD/ArGTC") - Notebooks
- Google Colab
- Kaggle
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README.md
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Finetuning code in the following notebook: [](https://colab.research.google.com/drive/106oPnGhe8B_BCgV6LnJbvVZNv4mCu9Zv?usp=sharing)
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### Full classification example
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
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```
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### Pipeline example
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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Finetuning code in the following notebook: [](https://colab.research.google.com/drive/106oPnGhe8B_BCgV6LnJbvVZNv4mCu9Zv?usp=sharing)
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### Full classification example (CPU)
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
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```
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### Pipeline example (CPU & GPU)
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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