Instructions to use guyhadad01/E5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use guyhadad01/E5-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="guyhadad01/E5-small")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("guyhadad01/E5-small") model = AutoModelForMaskedLM.from_pretrained("guyhadad01/E5-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e059241e9f916c0b9a3dbc49deb5b1f2398379e41f98a6042a7b44ebc3928dba
- Size of remote file:
- 472 MB
- SHA256:
- 8b1eabd77d190b17654c8c986e9239c763f0de2696fc13757ebbfea99d1ab898
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