Instructions to use Nehc/FakeMobile with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nehc/FakeMobile with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Nehc/FakeMobile")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Nehc/FakeMobile") model = AutoModelForSequenceClassification.from_pretrained("Nehc/FakeMobile", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| language: | |
| - ru | |
| widget: | |
| - text: "[CLS] Какая абонентская плата на тарифе Позвони маме? [SEP]" | |
| metrics: | |
| - loss: 0.704381 | |
| - accuracy: 1.000000 | |
| Start from 'DeepPavlov/rubert-base-cased' and finetuning on DUMBOT fake data (http://dumbot.ru/Home/MobileOperatorRate). | |
| 100 epoch | |
| on progress... | |