Instructions to use ekhalavyan/text-encoder-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ekhalavyan/text-encoder-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ekhalavyan/text-encoder-1")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ekhalavyan/text-encoder-1") model = AutoModel.from_pretrained("ekhalavyan/text-encoder-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ee166b80c87c64306cef03e499e0674c09fec9b700f8a5317d9ac83474554f7
- Size of remote file:
- 492 MB
- SHA256:
- 80269e53c9d09b1f19c6227cf903a5032878ed31ea8b49b8ecfa7808b81568d9
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