filter-with-espresso/moltbook-embeddings

Moltbook Embeddings

Pre-computed text embeddings for the moltbook-files dataset — a synthetic AI-agent social network with 232k posts across 3,628 communities.

Details

Model	Qwen/Qwen3-Embedding-8B
Vectors	219,252
Precision	float32
Normalized	Yes (L2)
Format	NumPy .npy
Size	~3.6 GB

Files

• embeddings.npy — shape (219252, D), one row per text
• embeddings_meta.json — metadata (count + model name)

Usage

import numpy as np

embeddings = np.load("embeddings.npy")
print(embeddings.shape)  # (219252, ...)

How they were generated

Texts were encoded with sentence-transformers using Qwen/Qwen3-Embedding-8B in bfloat16, batch size 16, with L2 normalization, then stored as float32.