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")# pip install -U transformers accelerate # 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
update wandb
Browse files- run_mlm_flax_stream.py +2 -2
run_mlm_flax_stream.py
CHANGED
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@@ -522,8 +522,8 @@ if __name__ == "__main__":
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# Enable Weight&Biases
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import wandb
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wandb.init(
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entity='
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project='
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sync_tensorboard=True,
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)
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wandb.config.update(training_args)
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# Enable Weight&Biases
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import wandb
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wandb.init(
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+
entity='munggok',
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project='roberta-indo-base',
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sync_tensorboard=True,
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)
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wandb.config.update(training_args)
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