Text Classification
Transformers
LiteRT
ONNX
Safetensors
bert
language
detection
classification
text-embeddings-inference
Instructions to use dewdev/language_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dewdev/language_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dewdev/language_detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dewdev/language_detection") model = AutoModelForSequenceClassification.from_pretrained("dewdev/language_detection") - Notebooks
- Google Colab
- Kaggle
Delete onnx/special_tokens.json
Browse files- onnx/special_tokens.json +0 -7
onnx/special_tokens.json
DELETED
|
@@ -1,7 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"unk_token": "[UNK]",
|
| 3 |
-
"sep_token": "[SEP]",
|
| 4 |
-
"pad_token": "[PAD]",
|
| 5 |
-
"cls_token": "[CLS]",
|
| 6 |
-
"mask_token": "[MASK]"
|
| 7 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|