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rubert-tiny2-russian-financial-sentiment
mxlcw/rubert-tiny2-russian-financial-sentiment
rubert-tiny2-russian-financial-sentiment is a text classification model from mxlcw. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
This is seara/rubert-tiny2-russian-sentiment model fine-tuned for sentiment classification of short Russian financial posts from Telegram channels.
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Jun 4, 2024
- Updated
- Nov 7, 2024
- SHA
- a02913e4
Try a prompt
Model card
From the Hugging Face model README
This is seara/rubert-tiny2-russian-sentiment model fine-tuned for sentiment classification of short Russian financial posts from Telegram channels.
The task is a multi-class classification with the following labels:
0: neutral
1: positive
2: negative
Usage
from transformers import pipeline
model = pipeline(model="mxlcw/rubert-tiny2-russian-economic-sentiment")
model("""На фоне санкций и дефицита госбюджета РФ компания Северсталь может
потерять доступ к европейским рынкам. Причина — избыток сырья,
из-за чего цены реализации могли снизиться, а также риск повышения
налоговой нагрузки на фоне дефицита госбюджета РФ — все это создает
неопределенность относительно результатов в 2023 году.""")
#[{'label': 'negative', 'score': 0.9207897186279297}]
Dataset
This model was trained on the following dataset:
- Telegram Financial Sentiment (ru)
An overview of the training data can be found here.
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- ru
- Hf Inference
- live
- Created
- Jun 4, 2024
- Updated
- Nov 7, 2024