Instructions to use McGill-NLP/dpr-statcan-metadata_encoder-basic_info_fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use McGill-NLP/dpr-statcan-metadata_encoder-basic_info_fr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="McGill-NLP/dpr-statcan-metadata_encoder-basic_info_fr")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("McGill-NLP/dpr-statcan-metadata_encoder-basic_info_fr") model = AutoModel.from_pretrained("McGill-NLP/dpr-statcan-metadata_encoder-basic_info_fr") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e29cff398e78df6eea42495fe349d343de5ff87d96f9a0130eabd60737032e31
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size 442514376
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