How to use mlx-community/all-MiniLM-L6-v2-4bit with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mlx-community/all-MiniLM-L6-v2-4bit") 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]
How to use mlx-community/all-MiniLM-L6-v2-4bit with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("mlx-community/all-MiniLM-L6-v2-4bit") model = AutoModel.from_pretrained("mlx-community/all-MiniLM-L6-v2-4bit")
How to use mlx-community/all-MiniLM-L6-v2-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir all-MiniLM-L6-v2-4bit mlx-community/all-MiniLM-L6-v2-4bit
