Sentence Similarity
Transformers
PyTorch
ONNX
Safetensors
xlm-roberta
feature-extraction
language
granite
embeddings
multilingual
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use ibm-granite/granite-embedding-107m-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-granite/granite-embedding-107m-multilingual with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ibm-granite/granite-embedding-107m-multilingual") model = AutoModel.from_pretrained("ibm-granite/granite-embedding-107m-multilingual", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ibm-granite/granite-embedding-107m-multilingual: direct link, hf CLI and curl.
- Browser
- Download file 770 MB
-
https://huggingface.co/ibm-granite/granite-embedding-107m-multilingual/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ibm-granite/granite-embedding-107m-multilingual/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ibm-granite/granite-embedding-107m-multilingual/resolve/main/pytorch_model.bin
770 MB
- Xet hash:
- 2263e6ea8173f4349123ef74d805adf46fb0c700db877a74fe5078be77a498e6
- Size of remote file:
- 770 MB
- SHA256:
- 30b74f885343f50c7769aac4df7a9f205c0eafe377d56401f80ba7ee5f20e78e
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