pixie-rune-v1 GGUF

GGUF format of telepix/PIXIE-Rune-v1.0 for use with CrispEmbed and Ollama.

Files

File Quantization Size
pixie-rune-v1-q4_k.gguf Q4_K 0 MB
pixie-rune-v1-q8_0.gguf Q8_0 0 MB
pixie-rune-v1.gguf F32 0 MB

Recommended: Q8_0 for quality (cos vs HF: cross-lingual OK), Q4_K for size (cross-lingual OK).

Quick Start

CrispEmbed

./crispembed -m pixie-rune-v1 "Hello world"
./crispembed-server -m pixie-rune-v1 --port 8080

Ollama (with CrispStrobe fork)

echo "FROM pixie-rune-v1-q8_0.gguf" > Modelfile
ollama create pixie-rune-v1 -f Modelfile
curl http://localhost:11434/api/embed -d '{"model":"pixie-rune-v1","input":["Hello world"]}'

Python (CrispEmbed)

from crispembed import CrispEmbed
model = CrispEmbed("pixie-rune-v1-q8_0.gguf")
vectors = model.encode(["Hello world", "Goodbye world"])

Model Details

Property Value
Architecture XLM-R
Parameters 560M
Embedding Dimension 1024
Layers 24
Pooling CLS
Tokenizer SentencePiece
Language multilingual
Q8_0 vs HuggingFace cross-lingual OK
Q4_K vs HuggingFace cross-lingual OK

Server API

CrispEmbed server supports four API dialects:

  • POST /embed -- native
  • POST /v1/embeddings -- OpenAI-compatible
  • POST /api/embed -- Ollama-compatible
  • POST /api/embeddings -- Ollama legacy

Credits

Provenance and EU AI Act Art. 53 note

  • Upstream model: telepix/PIXIE-Rune-v1.0 โ€” published by telepix.
  • Upstream licence: apache-2.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not.
  • What was done here: format conversion and/or quantisation only (GGUF/GGML). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
  • Training data: documented โ€” where it is documented at all โ€” by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository.
  • Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.
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