Instructions to use EricLiang98/MigBERT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EricLiang98/MigBERT-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="EricLiang98/MigBERT-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("EricLiang98/MigBERT-base") model = AutoModelForMaskedLM.from_pretrained("EricLiang98/MigBERT-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from EricLiang98/MigBERT-base: direct link, hf CLI and curl.
- Browser
- Download file 588 MB
-
https://huggingface.co/EricLiang98/MigBERT-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://EricLiang98/MigBERT-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/EricLiang98/MigBERT-base/resolve/main/pytorch_model.bin
588 MB
- Xet hash:
- ae660aea115a9d9920eab28e5692081284f54d2ca9f15ac2919e441c8244512a
- Size of remote file:
- 588 MB
- SHA256:
- b07e3892c61580bb7396603038ec5d983b17a25a894828a0e839ae7e2825c80d
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