Instructions to use kornwtp/ConGen-MiniLM-L12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kornwtp/ConGen-MiniLM-L12 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kornwtp/ConGen-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-MiniLM-L12 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kornwtp/ConGen-MiniLM-L12") model = AutoModel.from_pretrained("kornwtp/ConGen-MiniLM-L12", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kornwtp/ConGen-MiniLM-L12: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/kornwtp/ConGen-MiniLM-L12/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kornwtp/ConGen-MiniLM-L12/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kornwtp/ConGen-MiniLM-L12/resolve/main/pytorch_model.bin
134 MB
- Xet hash:
- 87e8f7e72dce39331daadacbcfb8eebac014744e00a877eeb8e1134dd4f23eb9
- Size of remote file:
- 134 MB
- SHA256:
- 5c582e53d88cd7c99e0fab2fabdef9cb765f2947009c5f4871bc6d7d03aa3383
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