Instructions to use RocioUrquijo/languagedetectionclassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RocioUrquijo/languagedetectionclassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RocioUrquijo/languagedetectionclassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RocioUrquijo/languagedetectionclassification") model = AutoModelForSequenceClassification.from_pretrained("RocioUrquijo/languagedetectionclassification") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:df259c551d62fd96432cda2f5115fa47a7c857a2de82b2a93017c4202597ef6a
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size 711503016
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