Instructions to use danielsaggau/bregman_base_ecthr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use danielsaggau/bregman_base_ecthr with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("danielsaggau/bregman_base_ecthr") 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 danielsaggau/bregman_base_ecthr with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("danielsaggau/bregman_base_ecthr") model = AutoModelForMultimodalLM.from_pretrained("danielsaggau/bregman_base_ecthr") - Notebooks
- Google Colab
- Kaggle