Text Classification
Transformers
Safetensors
bert
lid
Language Identification
African Languages
text-embeddings-inference
Instructions to use dsfsi/za-lid-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dsfsi/za-lid-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dsfsi/za-lid-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dsfsi/za-lid-bert") model = AutoModelForSequenceClassification.from_pretrained("dsfsi/za-lid-bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 218895389c615f13b2e5d53ca93fd7706952a306f1fa2163aee609d7ebddc1f8
- Size of remote file:
- 2.04 kB
- SHA256:
- 61112c990cb380852cdbe11a8b0eeaaecc2bbd875c2dfd9f32958d3e08bff1af
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