Instructions to use BM-K/KoMiniLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BM-K/KoMiniLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BM-K/KoMiniLM")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BM-K/KoMiniLM") model = AutoModel.from_pretrained("BM-K/KoMiniLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0bd6c2865cdb608078c33d2655f6ba95fec7d3e883ce52176634e712b8940a83
- Size of remote file:
- 93.2 MB
- SHA256:
- 04f8a7264589a174c734b977bdf6fe16ead653c14b906bbd62d539c8a69c1830
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