Text Classification
Transformers
PyTorch
TensorFlow
JAX
Safetensors
Russian
bert
sentiment-analysis
multi-class-classification
sentiment analysis
rubert
sentiment
tiny
russian
multiclass
classification
text-embeddings-inference
Instructions to use seara/rubert-tiny2-russian-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seara/rubert-tiny2-russian-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="seara/rubert-tiny2-russian-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("seara/rubert-tiny2-russian-sentiment") model = AutoModelForSequenceClassification.from_pretrained("seara/rubert-tiny2-russian-sentiment") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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oid sha256:989424a83d6816d853571fd48926906f723c28d65b962d31ceca6029781c737e
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size 116801868
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