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 training_args.bin from Donoe/NaijaMultilingualBank: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/Donoe/NaijaMultilingualBank/resolve/main/training_args.bin
- Command line
-
hf download hf://Donoe/NaijaMultilingualBank/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Donoe/NaijaMultilingualBank/resolve/main/training_args.bin
5.27 kB
- Xet hash:
- 3b7070da288110f2b5ff36a6abebd4f1090169923e1437f017c0dccfee8b58db
- Size of remote file:
- 5.27 kB
- SHA256:
- 116eb8b76bbfbc85d5ba1a9fc0610e01d7be8c306d1976bdddcd3bd8af3e0301
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