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 scaler.pt from anjandash/JavaBERT-mini: direct link, hf CLI and curl.
- Browser
- Download file 559 Bytes
-
https://huggingface.co/anjandash/JavaBERT-mini/resolve/main/scaler.pt
- Command line
-
hf download hf://anjandash/JavaBERT-mini/scaler.pt
-
curl -L -o scaler.pt https://huggingface.co/anjandash/JavaBERT-mini/resolve/main/scaler.pt
559 Bytes
- Xet hash:
- 1c9655349ee986bd1ae8113e89062208d1e8f453bc934ac8ecf07d59136d0b77
- Size of remote file:
- 559 Bytes
- SHA256:
- 61f32f894187fb542f29cbbe7f61fa211719166ef17c8a5665f9cdb762ff442f
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