Instructions to use sabaimran/ms-marco-MiniLM-L-6-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sabaimran/ms-marco-MiniLM-L-6-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sabaimran/ms-marco-MiniLM-L-6-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sabaimran/ms-marco-MiniLM-L-6-v2") model = AutoModelForSequenceClassification.from_pretrained("sabaimran/ms-marco-MiniLM-L-6-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sabaimran/ms-marco-MiniLM-L-6-v2: direct link, hf CLI and curl.
- Browser
- Download file 90.9 MB
-
https://huggingface.co/sabaimran/ms-marco-MiniLM-L-6-v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sabaimran/ms-marco-MiniLM-L-6-v2/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/sabaimran/ms-marco-MiniLM-L-6-v2/resolve/main/pytorch_model.bin
90.9 MB
- Xet hash:
- 09b4ad542fba5be09d0cb14ed521bf9d15324a3b2cacd403c3a77c22dbdd14b9
- Size of remote file:
- 90.9 MB
- SHA256:
- 3ae17b87eda3d184502a821fddff43d82feb7c206f665a851c491ec715b497ed
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