Views
No views yet
| File | Quantization | Size |
|---|---|---|
| arctic-embed-l-v2-q4_k.gguf | Q4_K | 0 MB |
| arctic-embed-l-v2-q8_0.gguf | Q8_0 | 0 MB |
| arctic-embed-l-v2.gguf | F32 | 0 MB |
1./crispembed -m arctic-embed-l-v2 "Hello world"
2./crispembed-server -m arctic-embed-l-v2 --port 80801echo "FROM arctic-embed-l-v2-q8_0.gguf" > Modelfile
2ollama create arctic-embed-l-v2 -f Modelfile
3curl http://localhost:11434/api/embed -d '{"model":"arctic-embed-l-v2","input":["Hello world"]}'1from crispembed import CrispEmbed
2model = CrispEmbed("arctic-embed-l-v2-q8_0.gguf")
3vectors = model.encode(["Hello world", "Goodbye world"])| Property | Value |
|---|---|
| Architecture | XLM-R |
| Parameters | 560M |
| Embedding Dimension | 1024 |
| Layers | 24 |
| Pooling | CLS |
| Tokenizer | SentencePiece |
| Language | en |
| Q8_0 vs HuggingFace | L2=1.0 |
| Q4_K vs HuggingFace | L2=1.0 |
POST /embed -- nativePOST /v1/embeddings -- OpenAI-compatiblePOST /api/embed -- Ollama-compatiblePOST /api/embeddings -- Ollama legacySnowflake.apache-2.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not.