Instructions to use kornwtp/ConGen-MiniLM-L6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kornwtp/ConGen-MiniLM-L6 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kornwtp/ConGen-MiniLM-L6") 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-L6 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kornwtp/ConGen-MiniLM-L6") model = AutoModel.from_pretrained("kornwtp/ConGen-MiniLM-L6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kornwtp/ConGen-MiniLM-L6: direct link, hf CLI and curl.
- Browser
- Download file 90.9 MB
-
https://huggingface.co/kornwtp/ConGen-MiniLM-L6/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kornwtp/ConGen-MiniLM-L6/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kornwtp/ConGen-MiniLM-L6/resolve/main/pytorch_model.bin
90.9 MB
- Xet hash:
- 9e90878ebb23dd1bdc92364cfd5785d95cb2d0a834fcbe78e6aed8fcf2d9e7ae
- Size of remote file:
- 90.9 MB
- SHA256:
- a37c9ceea0a1c06752522fcc6438a77908d002f0e99da43741341c2ce6a61f45
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