Instructions to use DataikuNLP/TinyBERT_General_4L_312D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DataikuNLP/TinyBERT_General_4L_312D with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DataikuNLP/TinyBERT_General_4L_312D", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from DataikuNLP/TinyBERT_General_4L_312D: direct link, hf CLI and curl.
- Browser
- Download file 57.4 MB
-
https://huggingface.co/DataikuNLP/TinyBERT_General_4L_312D/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://DataikuNLP/TinyBERT_General_4L_312D/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/DataikuNLP/TinyBERT_General_4L_312D/resolve/main/flax_model.msgpack
57.4 MB
- Xet hash:
- 3ae0000e519063059bf98cbe3c4a1747af2d09c4a293f1c879d3fb408c0a86dc
- Size of remote file:
- 57.4 MB
- SHA256:
- 031d75f61b5d4079f0d9be329f768d63ca4d4bc6600b9c6298fdaacd755da699
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