Instructions to use language-ml-lab/classification-azb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use language-ml-lab/classification-azb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="language-ml-lab/classification-azb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("language-ml-lab/classification-azb") model = AutoModelForSequenceClassification.from_pretrained("language-ml-lab/classification-azb") - Notebooks
- Google Colab
- Kaggle
Text Classification Model
- Type: Fine-tuned BERT-based text classification model
- Description: This model has been fine-tuned using AzerBERT for text classification tasks. It is designed to categorize text into one of the following four categories: literature, sports, history, and geography.
How to use
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="language-ml-lab/classification-azb")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("language-ml-lab/classification-azb")
model = AutoModelForSequenceClassification.from_pretrained("language-ml-lab/classification-azb")
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