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
Upload model.onnx
Browse files- onnx/model.onnx +3 -1
onnx/model.onnx
CHANGED
|
@@ -1 +1,3 @@
|
|
| 1 |
-
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e6b4cbc6c4c16da9e8820ab725e42f837ce64784e1aaa39f391be159aa988ff8
|
| 3 |
+
size 97945184
|