Instructions to use facebook/contriever-msmarco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/contriever-msmarco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/contriever-msmarco")# Load model directly from transformers import AutoTokenizer, Contriever tokenizer = AutoTokenizer.from_pretrained("facebook/contriever-msmarco") model = Contriever.from_pretrained("facebook/contriever-msmarco", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/contriever-msmarco: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/facebook/contriever-msmarco/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/contriever-msmarco/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/contriever-msmarco/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 8da157f85480a0267d89a56ca9e578c1e0b86872b4d4b4e354a8aeb5ae077c77
- Size of remote file:
- 438 MB
- SHA256:
- 08b88f3a3697877345669405c51a23f53ed90aa2bab441cd7b7b08659925eef8
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