Instructions to use fathan/indojave-codemixed-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fathan/indojave-codemixed-bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="fathan/indojave-codemixed-bert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("fathan/indojave-codemixed-bert-base") model = AutoModelForMaskedLM.from_pretrained("fathan/indojave-codemixed-bert-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Evaluation Results
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We train the data with 3 epochs and total steps of
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The following are the results obtained from the training:
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| train loss | eval loss | eval perplexity |
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| `code-mixed-ijebert` | BERT | 2.24 GB of text | 249 MB of text |
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## Evaluation Results
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We train the data with 3 epochs and total steps of 296K for 12 days.
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The following are the results obtained from the training:
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| train loss | eval loss | eval perplexity |
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