Instructions to use readerbench/RoBERT-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use readerbench/RoBERT-small with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("readerbench/RoBERT-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from readerbench/RoBERT-small: direct link, hf CLI and curl.
- Browser
- Download file 77.4 MB
-
https://huggingface.co/readerbench/RoBERT-small/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://readerbench/RoBERT-small/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/readerbench/RoBERT-small/resolve/main/flax_model.msgpack
77.4 MB
- Xet hash:
- da8ad99e77f7bc451dc3a758682c4f606f50cab29fec96af7735105872d5e2e4
- Size of remote file:
- 77.4 MB
- SHA256:
- d1f134930b8f378c06b947c767f4174b93cae5784b469a4262f5a47a01357245
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