Text Classification
Transformers
Safetensors
Chinese
Yue Chinese
modernbert
zhlid
text-embeddings-inference
Instructions to use MusubiAI/ZHLID with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MusubiAI/ZHLID with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MusubiAI/ZHLID")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MusubiAI/ZHLID") model = AutoModelForSequenceClassification.from_pretrained("MusubiAI/ZHLID", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7dc51793b9519db41014ffdada0de47d4e52c5764f884282e0d4b0860798e1a2
- Size of remote file:
- 299 MB
- SHA256:
- 41781315aaea335d672a6549f67b71449bd1a14a49e857cb7cddf82b93bfb2f9
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