Simple ASCII Art txtai Embeddings
A txtai embeddings database built from PinkPixel/ASCII-Art, transformed for semantic retrieval.
- Indexed column:
text— the system/user prompt text withSystem:andUser:labels removed. - Return column:
ascii-art— assistant ASCII art with surrounding Markdown code fences stripped. - Embedding model:
ibm-granite/granite-embedding-english-r2 - Dimensions: 768
- Rows: 1,221
Load and search
import json
from txtai.embeddings import Embeddings
repo_dir = "txtai_ascii_art_embeddings"
metadata = {}
with open(f"{repo_dir}/metadata.jsonl", "r", encoding="utf-8") as handle:
for line in handle:
row = json.loads(line)
metadata[row["id"]] = row
embeddings = Embeddings()
embeddings.load(repo_dir)
for result in embeddings.search("a cute kitten sitting down", limit=3):
row = metadata[str(result["id"])]
print(result["score"])
print(row["text"])
print(row["ascii-art"])
Files
config.json,embeddings,documents: txtai database files.metadata.jsonl: id-aligned prompt and ASCII-art records.embedding_config.json: source/model/build metadata.
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Model tree for sayshara/simple-ascii-art-embeddings
Base model
ibm-granite/granite-embedding-english-r2
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sayshara/simple-ascii-art-embeddings") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3]