# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka")
model = AutoModelForSequenceClassification.from_pretrained("seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka", device_map="auto")Quick Links
RuBERT for Sentiment Analysis of study feedback
This is a blanchefort/rubert-base-cased-sentiment-rurewiews model finetuned for the subject area of study process feedback. Based on DeepPavlov/rubert-base-cased-conversational model.
From MOAD.dev with <3
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka")