Text Classification
Transformers
Safetensors
xlm-roberta
intent-classification
banking
multilingual
nlp
yoruba
hausa
igbo
nigeria
text-embeddings-inference
Instructions to use Donoe/NaijaMultilingualBank with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Donoe/NaijaMultilingualBank with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Donoe/NaijaMultilingualBank")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Donoe/NaijaMultilingualBank") model = AutoModelForSequenceClassification.from_pretrained("Donoe/NaijaMultilingualBank", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Donoe/NaijaMultilingualBank: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/Donoe/NaijaMultilingualBank/resolve/main/tokenizer.json
- Command line
-
hf download hf://Donoe/NaijaMultilingualBank/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Donoe/NaijaMultilingualBank/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 30d4d8e239dc122dc10fe0c296f250ba20881f621a97fbd62c0a5eec3ea7469e
- Size of remote file:
- 17.1 MB
- SHA256:
- 2687cc191964de4bb7f4a43b29e7398decc0661f77e860d9c69d77a1bf6c5fdf
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