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
Download training_args.bin from firqaaa/indo-biobert-base-uncased: direct link, hf CLI and curl.
- Browser
- Download file 1.78 kB
-
https://huggingface.co/firqaaa/indo-biobert-base-uncased/resolve/main/training_args.bin
- Command line
-
hf download hf://firqaaa/indo-biobert-base-uncased/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/firqaaa/indo-biobert-base-uncased/resolve/main/training_args.bin
1.78 kB
- Xet hash:
- 99eacd6572b8d156dde762f21707b9593f7bc0197e6cf3cac859c51f66213425
- Size of remote file:
- 1.78 kB
- SHA256:
- 76aa787f4c0bd59558b4746ff2add9faa8cdb99d3a6123124d3a3594a66db240
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