Instructions to use Manirathinam21/Multilingual_lang_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Manirathinam21/Multilingual_lang_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Manirathinam21/Multilingual_lang_detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Manirathinam21/Multilingual_lang_detection") model = AutoModelForSequenceClassification.from_pretrained("Manirathinam21/Multilingual_lang_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scheduler.pt from Manirathinam21/Multilingual_lang_detection: direct link, hf CLI and curl.
- Browser
- Download file 627 Bytes
-
https://huggingface.co/Manirathinam21/Multilingual_lang_detection/resolve/main/scheduler.pt
- Command line
-
hf download hf://Manirathinam21/Multilingual_lang_detection/scheduler.pt
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curl -L -o scheduler.pt https://huggingface.co/Manirathinam21/Multilingual_lang_detection/resolve/main/scheduler.pt
627 Bytes
- Xet hash:
- 05cd0466cb3de4939b9d3c38107d05ffda4f01cde47621533a41875bbefe6f85
- Size of remote file:
- 627 Bytes
- SHA256:
- 13e7b6020e24eba42d999faa1a6eda8c46b428b3cca3741db915220afbe681ba
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