Feature Extraction
Transformers
PyTorch
Danish
bert
BERT
encoder
embeddings
TiME
size:xs
text-embeddings-inference
Instructions to use dschulmeist/TiME-da-xs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dschulmeist/TiME-da-xs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dschulmeist/TiME-da-xs")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dschulmeist/TiME-da-xs") model = AutoModel.from_pretrained("dschulmeist/TiME-da-xs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0ee960c656713071586240aabefe782b478a401ea2c9c18425d5e222c0e5640
- Size of remote file:
- 414 MB
- SHA256:
- 7bdc406afd5bf55173ce9d269632ac930919599ef58db64e9eb1c577c7763848
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