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 tokenizer.json from nlpai-lab/MixLID: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/nlpai-lab/MixLID/resolve/main/tokenizer.json
- Command line
-
hf download hf://nlpai-lab/MixLID/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/nlpai-lab/MixLID/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- d91de22e35bd8cdca71c7f5afdcf16692aa26e84573c53e890272de39ee9fc78
- Size of remote file:
- 34.4 MB
- SHA256:
- a919df3596ecc3da31343106620dc367df9b12fb41c4b96e8ad773faaade7b5b
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