README.md

metadata

library_name: transformers
license: apache-2.0
language:
  - en
tags:
  - fill-mask
  - masked-lm
  - long-context
  - modernbert
  - mlx
pipeline_tag: fill-mask
inference: false

mlx-community/answerdotai-ModernBERT-base-4bit

The Model mlx-community/answerdotai-ModernBERT-base-4bit was converted to MLX format from answerdotai/ModernBERT-base using mlx-lm version 0.0.3.

Use with mlx

pip install mlx-embeddings

from mlx_embeddings import load, generate
import mlx.core as mx

model, tokenizer = load("mlx-community/answerdotai-ModernBERT-base-4bit")

# For text embeddings
output = generate(model, processor, texts=["I like grapes", "I like fruits"])
embeddings = output.text_embeds  # Normalized embeddings

# Compute dot product between normalized embeddings
similarity_matrix = mx.matmul(embeddings, embeddings.T)

print("Similarity matrix between texts:")
print(similarity_matrix)