Text Classification
Transformers
PyTorch
TensorFlow
JAX
Safetensors
Russian
bert
sentiment-analysis
multi-label-classification
sentiment analysis
rubert
sentiment
tiny
russian
multilabel
classification
emotion-classification
emotion-recognition
emotion
emotion-detection
text-embeddings-inference
Instructions to use seara/rubert-tiny2-russian-emotion-detection-cedr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seara/rubert-tiny2-russian-emotion-detection-cedr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="seara/rubert-tiny2-russian-emotion-detection-cedr")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("seara/rubert-tiny2-russian-emotion-detection-cedr") model = AutoModelForSequenceClassification.from_pretrained("seara/rubert-tiny2-russian-emotion-detection-cedr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -15,6 +15,8 @@ tags:
|
|
| 15 |
- emotion-classification
|
| 16 |
- emotion-recognition
|
| 17 |
- russian
|
|
|
|
|
|
|
| 18 |
datasets:
|
| 19 |
- cedr
|
| 20 |
---
|
|
|
|
| 15 |
- emotion-classification
|
| 16 |
- emotion-recognition
|
| 17 |
- russian
|
| 18 |
+
- classification
|
| 19 |
+
- multilabel
|
| 20 |
datasets:
|
| 21 |
- cedr
|
| 22 |
---
|