Sentence Similarity
Transformers
Safetensors
Vietnamese
sai_embedding
feature-extraction
embeddings
retrieval
llm2vec
matryoshka
custom-code
custom_code
Instructions to use thongbuind/SAI-Embedding_100M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thongbuind/SAI-Embedding_100M with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("thongbuind/SAI-Embedding_100M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from thongbuind/SAI-Embedding_100M: direct link, hf CLI and curl.
- Browser
- Download file 157 kB
-
https://huggingface.co/thongbuind/SAI-Embedding_100M/resolve/main/tokenizer.model
- Command line
-
hf download hf://thongbuind/SAI-Embedding_100M/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/thongbuind/SAI-Embedding_100M/resolve/main/tokenizer.model
157 kB
- Xet hash:
- fcbc32b13046a2c01de291b6119b9c6c38431a9feb73935b846ec017219d150f
- Size of remote file:
- 157 kB
- SHA256:
- 3eb2e8f55e0472fbe6c5f597d601746934e69542b5238a18852132761c03a9ac
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