Instructions to use ielabgroup/ToRoDer-msmarco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ielabgroup/ToRoDer-msmarco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ielabgroup/ToRoDer-msmarco")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ielabgroup/ToRoDer-msmarco") model = AutoModel.from_pretrained("ielabgroup/ToRoDer-msmarco") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6050b76064f4409399962d2fdf588aaa1d8c01db643264df25371d409a2e9b25
- Size of remote file:
- 438 MB
- SHA256:
- 0f22ce997b49be041660706457bcd17ac36f7c9f040e752b0677bff32309c1ac
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