# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("spolivin/lang-recogn-model")
model = AutoModelForSequenceClassification.from_pretrained("spolivin/lang-recogn-model")Quick Links
Language Detection Model
The model presented in the following repository represents a fine-tuned version of BertForSequenceClassification
pretrained on multilingual texts.
Training/fine-tuning
The model has been fine-tuned based on Language Detection dataset found on Kaggle. The entire process of the dataset analysis as well as a complete description of the training procedure can be found in one of my Kaggle notebooks which has been used for the purpose of a faster model training on GPU.
Supported languages
The model has been fine-tuned to detect one of the following 17 languages:
- Arabic
- Danish
- Dutch
- English
- French
- German
- Greek
- Hindi
- Italian
- Kannada
- Malayalam
- Portugeese
- Russian
- Spanish
- Sweedish
- Tamil
- Turkish
References
- Downloads last month
- 6
Model tree for spolivin/lang-recogn-model
Base model
google-bert/bert-base-multilingual-uncased
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="spolivin/lang-recogn-model")