Instructions to use acul3/roberta-base-indo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use acul3/roberta-base-indo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="acul3/roberta-base-indo")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("acul3/roberta-base-indo") model = AutoModelForMaskedLM.from_pretrained("acul3/roberta-base-indo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add run.sh
Browse files
run.sh
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# From https://arxiv.org/pdf/1907.11692.pdf
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##python3 -c "import jax; print('TPUs', jax.device_count())"
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python3 run_mlm_flax.py \
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--output_dir="./outputs" \
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--model_type="roberta" \
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--config_name="./configs/base" \
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# From https://arxiv.org/pdf/1907.11692.pdf
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##python3 -c "import jax; print('TPUs', jax.device_count())"
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tmux new-session -d -s 0 python3 run_mlm_flax.py \
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--output_dir="./outputs" \
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--model_type="roberta" \
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--config_name="./configs/base" \
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