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")# 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
File size: 270 Bytes
af38e1d | 1 2 3 4 5 6 | from transformers import TFAutoModelForSequenceClassification
checkpoint_path = "/Users/anjandash/Desktop/HF_MODELS/JavaBERT-small"
tf_model = TFAutoModelForSequenceClassification.from_pretrained(checkpoint_path, from_pt=True)
tf_model.save_pretrained(checkpoint_path)
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