Instructions to use whitefoxredhell/language_identification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whitefoxredhell/language_identification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="whitefoxredhell/language_identification")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("whitefoxredhell/language_identification") model = AutoModelForSeq2SeqLM.from_pretrained("whitefoxredhell/language_identification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1cd2b800baf4ea4ddebe13d40a89798a848b2fd5d4e4a89f85163b7bb3ff5dfd
- Size of remote file:
- 588 MB
- SHA256:
- cd5d4a90cdc29a67ac74bd7bd931140e597ce20a1b637c34ee1927d6fd44a353
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