Instructions to use jeang/bert-finetuned-sentence-classification-toy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jeang/bert-finetuned-sentence-classification-toy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jeang/bert-finetuned-sentence-classification-toy")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jeang/bert-finetuned-sentence-classification-toy") model = AutoModelForSequenceClassification.from_pretrained("jeang/bert-finetuned-sentence-classification-toy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
This model is a demonstration of the [Ernie library] (https://github.com/labteral/ernie) for fine-tuning sentence classification models. The base model is bert-base-uncased. The dataset for fine-tuning consists of two labeled example sentences. Because this is a toy example, we do not recommend it for anything other than for demonstrating the Ernie integration with Huggingface Hub.
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