Instructions to use dilanjt/java-javascript_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dilanjt/java-javascript_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dilanjt/java-javascript_model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dilanjt/java-javascript_model") model = AutoModelForMaskedLM.from_pretrained("dilanjt/java-javascript_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 402133e4de23322cf094fc7d60d74b5bf3eb95204d8018c57488c7b6f3735d80
- Size of remote file:
- 3.64 kB
- SHA256:
- 991780752301fd8441a53b7d70f02ce3b3671ffa91d79c7e633013e0b539f9ef
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