Instructions to use LocalDoc/language_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LocalDoc/language_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LocalDoc/language_detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LocalDoc/language_detection") model = AutoModelForSequenceClassification.from_pretrained("LocalDoc/language_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from LocalDoc/language_detection: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/LocalDoc/language_detection/resolve/main/model.safetensors
- Command line
-
hf download hf://LocalDoc/language_detection/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/LocalDoc/language_detection/resolve/main/model.safetensors
1.11 GB
- Xet hash:
- 8730105193abe963a011a1ae515e02785a8476c52dc28a7803fa04f6eb94706b
- Size of remote file:
- 1.11 GB
- SHA256:
- eb043b97633c7ccb131efdad5ea0c82ffe6b66d27f6dcf6c80bda5c71d8579b4
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