Text Classification
Transformers
PyTorch
Safetensors
Russian
bert
russian
classification
toxicity
multilabel
text-embeddings-inference
Instructions to use cointegrated/rubert-tiny-toxicity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/rubert-tiny-toxicity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cointegrated/rubert-tiny-toxicity")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cointegrated/rubert-tiny-toxicity") model = AutoModelForSequenceClassification.from_pretrained("cointegrated/rubert-tiny-toxicity") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
f9844b9
1
Parent(s): 01d80d4
Train the model for 15 epochs
Browse files- pytorch_model.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 47168503
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3acf3c98b1f80cfd8cdbf45178993636be89c320df713cbcac0f25d31ab36b3d
|
| 3 |
size 47168503
|