Instructions to use dilanjt/java-javascript-modelv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dilanjt/java-javascript-modelv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dilanjt/java-javascript-modelv2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dilanjt/java-javascript-modelv2") model = AutoModelForMaskedLM.from_pretrained("dilanjt/java-javascript-modelv2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9cbd30e176b9eb33b6611bf792e3f8671d98ce2a5587e18345995abe9aea822
- Size of remote file:
- 499 MB
- SHA256:
- f83fa1f92e6dff75d13fe3ce69dedd9c712e0e2483bcb899bdbc9504bc8c7372
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