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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dewdev/language_detection") model = AutoModelForSequenceClassification.from_pretrained("dewdev/language_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload tokenizer.json
Verified signature60e22d8
-
Upload 4 files
Verified signature05493e8 -
Upload 4 files
Verified signature9a1949f -
Upload model.onnx
Verified signatured357c57 -
Upload model.onnx
Verified signaturecd04eeb -
Delete language_detection.onnx
Verified signature0940367
-
Upload 4 files
Verified signature75b6b78 -
Create tflite/model.tflite
Verified signaturef295f05 -
Upload 3 files
Verified signaturebdd936f -
Upload 4 files
Verified signature6d6cf74 -
Upload model.onnx
Verified signature04f1324 -
Upload model.onnx
Verified signaturece2c8e6
-
Update README.md
Verified signature58ed1f8 -
Upload model.onnx
Verified signatureb339096 -
Create onnx/model.onnx
Verified signature345cce9 -
Upload 9 files
Verified signaturea53ef18 -
initial commit
Verified signature915f601