Instructions to use KennethEnevoldsen/dfm-sentence-encoder-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KennethEnevoldsen/dfm-sentence-encoder-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="KennethEnevoldsen/dfm-sentence-encoder-large")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("KennethEnevoldsen/dfm-sentence-encoder-large") model = AutoModel.from_pretrained("KennethEnevoldsen/dfm-sentence-encoder-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0da7e07a391d5e40f88c78435ee68470fcfda8c68bd634c50f98e9d53be6f8e8
- Size of remote file:
- 1.63 GB
- SHA256:
- efd6af53a499aea8fd88afa68771609bf18d54610ef7208bc859f16ca9735917
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