Instructions to use firqaaa/indo-biobert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use firqaaa/indo-biobert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="firqaaa/indo-biobert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("firqaaa/indo-biobert-base-uncased") model = AutoModelForMaskedLM.from_pretrained("firqaaa/indo-biobert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ecbdf63d9a6786b0c911df6da8af76364b2f4a0db678d7614688b8c57617327d
- Size of remote file:
- 334 MB
- SHA256:
- 507d17bcdf20c601c6d3ca6f62b4240e27584c85c555c0e863832cced7f35111
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