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:
- 2df4e413506d8c7babad5def274752c12a6f16ad6699819afe691c0e5062c76f
- Size of remote file:
- 17.1 MB
- SHA256:
- 9af54fe549c06785a9c79eaa3f0c67144a19c56e1370229244d49c8a22fcaaec
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