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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a64f3e420f40a2f3c81d918eb6e573e2ea5ecd2a6425699fdf3c4a6871837a3
- Size of remote file:
- 499 MB
- SHA256:
- f2dc37dbb30e06214e2155f63170bfa3fbe5c03a3d45dd59b7bdd37d18c8db9f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.