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 ·
635187b
1
Parent(s): 6bc8969
Update config.json
Browse files- config.json +1 -0
config.json
CHANGED
|
@@ -32,6 +32,7 @@
|
|
| 32 |
"num_hidden_layers": 3,
|
| 33 |
"pad_token_id": 0,
|
| 34 |
"position_embedding_type": "absolute",
|
|
|
|
| 35 |
"torch_dtype": "float32",
|
| 36 |
"transformers_version": "4.9.0",
|
| 37 |
"type_vocab_size": 2,
|
|
|
|
| 32 |
"num_hidden_layers": 3,
|
| 33 |
"pad_token_id": 0,
|
| 34 |
"position_embedding_type": "absolute",
|
| 35 |
+
"problem_type": "multi_label_classification",
|
| 36 |
"torch_dtype": "float32",
|
| 37 |
"transformers_version": "4.9.0",
|
| 38 |
"type_vocab_size": 2,
|