Instructions to use krunchykat/test-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krunchykat/test-embedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="krunchykat/test-embedding")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("krunchykat/test-embedding") model = AutoModel.from_pretrained("krunchykat/test-embedding", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e3c5fb70068d188a817de285eba49fae320e7dca598888516cf636a11a3262c
- Size of remote file:
- 135 MB
- SHA256:
- d4dac4bfa07450b7773f47d600b0a50c424f3d76afa0f7e2253fced5614447c2
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