mlx-community/nomicai-modernbert-embed-base-bf16

🤗 Hugging Face 来源sentence-similarityapache-2.0149M 参数298 MBsafetensors✓ 1 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo mlx-community/nomicai-modernbert-embed-base-bf16 ./model-folder
需要做种者 →

mlx-community/modernbert-embed-base-bf16

The Model mlx-community/nomicai-modernbert-embed-base-bf16 was converted to MLX format from nomic-ai/modernbert-embed-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/nomicai-modernbert-embed-base-bf16")

# 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)