Instructions to use nreimers/BERT-Tiny_L-2_H-128_A-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nreimers/BERT-Tiny_L-2_H-128_A-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nreimers/BERT-Tiny_L-2_H-128_A-2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nreimers/BERT-Tiny_L-2_H-128_A-2") model = AutoModel.from_pretrained("nreimers/BERT-Tiny_L-2_H-128_A-2") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 617614fa55920c1de5721be31d471f642ea7dbe5e86769b6f6ee6cb18c86c2d0
- Size of remote file:
- 17.7 MB
- SHA256:
- 29176df5fad1e487f08b7701bd72b30f2342b4614c5ffeede6365fc1520ba34c
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