Text Classification
Transformers
Safetensors
Russian
bert
sentiment-analysis
multi-class-classification
financial
telegram
rubert
sentiment
tiny
russian
multiclass
classification
Text Classification
text-embeddings-inference
Instructions to use mxlcw/rubert-tiny2-russian-financial-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mxlcw/rubert-tiny2-russian-financial-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mxlcw/rubert-tiny2-russian-financial-sentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mxlcw/rubert-tiny2-russian-financial-sentiment") model = AutoModelForSequenceClassification.from_pretrained("mxlcw/rubert-tiny2-russian-financial-sentiment", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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