Instructions to use SparseCL/UAE-SparseCL-msmarco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SparseCL/UAE-SparseCL-msmarco with Transformers:
# Load model directly from transformers import AutoTokenizer, our_BertForCL tokenizer = AutoTokenizer.from_pretrained("SparseCL/UAE-SparseCL-msmarco") model = our_BertForCL.from_pretrained("SparseCL/UAE-SparseCL-msmarco", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb13c342638ba84449534f965455b25f96d5254db6db64d1fe5f34dbbb011a88
- Size of remote file:
- 1.34 GB
- SHA256:
- 2ac992db1a32805eccc5b6afd1187aca0a040984b9b0e6427524de3ba902ee65
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