Instructions to use mjavadmt/simple_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mjavadmt/simple_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mjavadmt/simple_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mjavadmt/simple_classification") model = AutoModelForSequenceClassification.from_pretrained("mjavadmt/simple_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| datasets: | |
| - GEM/xwikis | |
| metrics: | |
| - bleu | |
| widget: | |
| - text: I'm going to stay here | |
| - text: this is fantastic | |
| - text: what a bad sh | |
| pipeline_tag: text-classification | |