Instructions to use McGill-NLP/dpr-statcan-conversation_encoder-basic_and_member with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use McGill-NLP/dpr-statcan-conversation_encoder-basic_and_member with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="McGill-NLP/dpr-statcan-conversation_encoder-basic_and_member")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("McGill-NLP/dpr-statcan-conversation_encoder-basic_and_member") model = AutoModel.from_pretrained("McGill-NLP/dpr-statcan-conversation_encoder-basic_and_member") - Notebooks
- Google Colab
- Kaggle
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