Instructions to use Howardxuan/m3e-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Howardxuan/m3e-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Howardxuan/m3e-small")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Howardxuan/m3e-small") model = AutoModel.from_pretrained("Howardxuan/m3e-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a53195248695e6ca2393f43e1dc65e9fb8f9b507efd8c492aef56e67b889d0d
- Size of remote file:
- 95.8 MB
- SHA256:
- 78fbbe22d9bc31a59a95dfd1b1ceb4f9b65cf4ddf54d948a20952789c9ec4973
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