Text Classification
Transformers
PyTorch
Safetensors
Russian
bert
sentiment-analysis
multi-class-classification
sentiment analysis
rubert
sentiment
tiny
russian
multiclass
classification
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("mikhmanoff/bert_ru")
model = AutoModelForSequenceClassification.from_pretrained("mikhmanoff/bert_ru")Quick Links
The task is a multi-class classification with the following labels:
0: neutral
1: positive
2: negative
Label to Russian label:
neutral: нейтральный
positive: позитивный
negative: негативный
Usage
from transformers import pipeline
model = pipeline(model="seara/rubert-tiny2-russian-sentiment")
model("Привет, ты мне нравишься!")
# [{'label': 'positive', 'score': 0.9398769736289978}]
- Downloads last month
- 6
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mikhmanoff/bert_ru")