Instructions to use kornwtp/ConGen-Multilingual-MiniLM-L12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kornwtp/ConGen-Multilingual-MiniLM-L12 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kornwtp/ConGen-Multilingual-MiniLM-L12") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use kornwtp/ConGen-Multilingual-MiniLM-L12 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kornwtp/ConGen-Multilingual-MiniLM-L12") model = AutoModel.from_pretrained("kornwtp/ConGen-Multilingual-MiniLM-L12", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kornwtp/ConGen-Multilingual-MiniLM-L12: direct link, hf CLI and curl.
- Browser
- Download file 471 MB
-
https://huggingface.co/kornwtp/ConGen-Multilingual-MiniLM-L12/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kornwtp/ConGen-Multilingual-MiniLM-L12/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kornwtp/ConGen-Multilingual-MiniLM-L12/resolve/main/pytorch_model.bin
471 MB
- Xet hash:
- 46b9878951d61995534747325a0b0d78de5d7c17d45b7dd785d27fffe0c7e392
- Size of remote file:
- 471 MB
- SHA256:
- a374d0343d784c2366d3ea3f34ed670367d2b3cfa5ed9b06481e92459d4620bd
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