Instructions to use anjandash/JavaBERT-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anjandash/JavaBERT-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anjandash/JavaBERT-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anjandash/JavaBERT-small") model = AutoModelForSequenceClassification.from_pretrained("anjandash/JavaBERT-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from anjandash/JavaBERT-small: direct link, hf CLI and curl.
- Browser
- Download file 3.12 kB
-
https://huggingface.co/anjandash/JavaBERT-small/resolve/main/training_args.bin
- Command line
-
hf download hf://anjandash/JavaBERT-small/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/anjandash/JavaBERT-small/resolve/main/training_args.bin
3.12 kB
- Xet hash:
- e29ad44f4510df29a67da47c1bd0d3471649ce9288280de4ad410bdd1a41d926
- Size of remote file:
- 3.12 kB
- SHA256:
- 20995a35255e755147fe73406a5b5e0d9face3602f8680abb97f54e0f4ea86b1
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