Instructions to use team-lucid/jina-bert-small-ko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use team-lucid/jina-bert-small-ko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="team-lucid/jina-bert-small-ko", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("team-lucid/jina-bert-small-ko", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("team-lucid/jina-bert-small-ko", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe70c9128d27afd5b2156db821669ab7488d2031c356fa78f8237a06ab1756dc
- Size of remote file:
- 134 MB
- SHA256:
- 92767102cac9bbddcca4460c43c58d584d9c28c9e435b740c428f8a269cfce64
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