Instructions to use Ran-Mewo/e5-small-v2-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ran-Mewo/e5-small-v2-quantized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Ran-Mewo/e5-small-v2-quantized")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Ran-Mewo/e5-small-v2-quantized") model = AutoModel.from_pretrained("Ran-Mewo/e5-small-v2-quantized") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6018e464c38f5e2488efbdc71448191e125199e3bb87544b2faf76b29dfa511
- Size of remote file:
- 134 MB
- SHA256:
- 4790fed2919e70bff573d01cd3aede75970f219ab4c0b0aeadd0f4b98084a17d
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