Instructions to use seongwoon/labor_space_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seongwoon/labor_space_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="seongwoon/labor_space_bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("seongwoon/labor_space_bert") model = AutoModelForMaskedLM.from_pretrained("seongwoon/labor_space_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from seongwoon/labor_space_bert: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/seongwoon/labor_space_bert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://seongwoon/labor_space_bert/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/seongwoon/labor_space_bert/resolve/main/pytorch_model.bin
438 MB
- Size of remote file:
- 438 MB
- SHA256:
- e9487f07e3cc47fafd63f96d025b879c3437dbc1c54cd5fd707c7ef74a7b2d4a
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