Instructions to use lgessler/microbert-indonesian-mxp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lgessler/microbert-indonesian-mxp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="lgessler/microbert-indonesian-mxp")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("lgessler/microbert-indonesian-mxp") model = AutoModel.from_pretrained("lgessler/microbert-indonesian-mxp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff93448202c367006d1b91f2f158a80c3e53978f59232ee15763f6291664f11e
- Size of remote file:
- 6.04 MB
- SHA256:
- b6f96a8253538dc3ef3727e94932e7a918d0ee2ba0ff69178af058e26f516514
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