Instructions to use emre/java-RoBERTa-Tara-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emre/java-RoBERTa-Tara-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="emre/java-RoBERTa-Tara-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("emre/java-RoBERTa-Tara-small") model = AutoModelForMaskedLM.from_pretrained("emre/java-RoBERTa-Tara-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -20,6 +20,6 @@ A MLM (Masked Language Model) objective was used to train this model.
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### Usage
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```python
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from transformers import pipeline
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pipe = pipeline('fill-mask', model='
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output = pipe(CODE) # Replace with Java code; Use '[MASK]' to mask tokens/words in the code.
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```
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### Usage
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```python
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from transformers import pipeline
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pipe = pipeline('fill-mask', model='emre/java-RoBERTa-Tara-small')
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output = pipe(CODE) # Replace with Java code; Use '[MASK]' to mask tokens/words in the code.
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```
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