Instructions to use seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seninoseno/rubert-base-cased-sentiment-study-feedbacks-solyanka with Transformers:
# 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")# 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") - Notebooks
- Google Colab
- Kaggle
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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