Instructions to use mosaicml/mosaic-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mosaicml/mosaic-bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mosaicml/mosaic-bert-base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mosaicml/mosaic-bert-base", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("mosaicml/mosaic-bert-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mosaicml/mosaic-bert-base: direct link, hf CLI and curl.
- Browser
- Download file 550 MB
-
https://huggingface.co/mosaicml/mosaic-bert-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mosaicml/mosaic-bert-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mosaicml/mosaic-bert-base/resolve/main/pytorch_model.bin
550 MB
- Xet hash:
- 39f8af5c8294f567f726cd9574d730728ab6426b7939cf2904d4f27e26a2aa3d
- Size of remote file:
- 550 MB
- SHA256:
- 32c76f325d9cf0b17ce112c6565f85b5415c50813d3ed89c510b94d2ac4dffd8
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