Text Classification
Transformers
PyTorch
Safetensors
Russian
English
bert
russian
classification
emotion
emotion-detection
emotion-recognition
multiclass
text-embeddings-inference
Instructions to use Djacon/rubert-tiny2-russian-emotion-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Djacon/rubert-tiny2-russian-emotion-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Djacon/rubert-tiny2-russian-emotion-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Djacon/rubert-tiny2-russian-emotion-detection") model = AutoModelForSequenceClassification.from_pretrained("Djacon/rubert-tiny2-russian-emotion-detection") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7ea59f76554866d81c5edefc523fc1226f265e6c3946d23e0792f7476cbd831c
|
| 3 |
+
size 116810632
|