Instructions to use anjandash/JavaBERT-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anjandash/JavaBERT-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anjandash/JavaBERT-mini")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anjandash/JavaBERT-mini") model = AutoModelForSequenceClassification.from_pretrained("anjandash/JavaBERT-mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from anjandash/JavaBERT-mini: direct link, hf CLI and curl.
- Browser
- Download file 3.12 kB
-
https://huggingface.co/anjandash/JavaBERT-mini/resolve/main/training_args.bin
- Command line
-
hf download hf://anjandash/JavaBERT-mini/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/anjandash/JavaBERT-mini/resolve/main/training_args.bin
3.12 kB
- Xet hash:
- f73c4df86313d2a854e00aa66f1e0b3b2ce028279128c12bee5fca115a8ddb06
- Size of remote file:
- 3.12 kB
- SHA256:
- 7628d68fa5e1ff99fb88c4d7a4d4a6a705ba610323f735887ff2919aecec2661
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