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
File size: 337 Bytes
ee1ad0d 7e25195 d3e025c 7e25195 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ---
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...
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