Token Classification
Transformers
Safetensors
modernbert
lid
language-identification
multilingual
code-switching
code-mixing
custom_code
Instructions to use nlpai-lab/MixLID with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpai-lab/MixLID with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nlpai-lab/MixLID", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nlpai-lab/MixLID", trust_remote_code=True) model = AutoModelForTokenClassification.from_pretrained("nlpai-lab/MixLID", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download assets/image.png from nlpai-lab/MixLID: direct link, hf CLI and curl.
- Browser
- Download file 186 kB
-
https://huggingface.co/nlpai-lab/MixLID/resolve/main/assets/image.png
- Command line
-
hf download hf://nlpai-lab/MixLID/assets/image.png
-
curl -L -o image.png https://huggingface.co/nlpai-lab/MixLID/resolve/main/assets/image.png
186 kB

- Xet hash:
- 880b4e1019c80ce0ec9fd2d9fd901b910feb0d504df58222a3ec023a704db6fb
- Size of remote file:
- 186 kB
- SHA256:
- 19684e9b49f54d9ab693708f494c3fbb017d8b25f3d46b9f65c9f60b3d7cd9c6
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