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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 174 Bytes
75b6b78 | 1 2 3 4 5 6 7 8 9 10 | {
"model_max_length": 512,
"padding_side": "right",
"truncation_side": "right",
"model_input_names": [
"input_ids",
"attention_mask"
],
"use_fast": true
} |