Instructions to use epwalsh/bert-xsmall-dummy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use epwalsh/bert-xsmall-dummy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="epwalsh/bert-xsmall-dummy")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("epwalsh/bert-xsmall-dummy") model = AutoModel.from_pretrained("epwalsh/bert-xsmall-dummy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from epwalsh/bert-xsmall-dummy: direct link, hf CLI and curl.
- Browser
- Download file 77.4 kB
-
https://huggingface.co/epwalsh/bert-xsmall-dummy/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://epwalsh/bert-xsmall-dummy/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/epwalsh/bert-xsmall-dummy/resolve/main/flax_model.msgpack
77.4 kB
- Xet hash:
- 2cba96b0bc517116d06eeaf108e54d611826e893a4e31510ddceea5fade8df88
- Size of remote file:
- 77.4 kB
- SHA256:
- f52b496747cc128fd502e8b8a83fceb7da1a601d8160595b475d47259cf21e76
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