Feature Extraction
GGUF
English
multilingual
embedding
sentence-similarity
llama.cpp
autoround
intel
matryoshka
Instructions to use webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible embeddings server: llama serve -hf webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF:Q4_K_S --embeddings
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible embeddings server: llama serve -hf webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF:Q4_K_S --embeddings
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible embeddings server: ./llama-server -hf webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF:Q4_K_S --embeddings
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible embeddings server: ./build/bin/llama-server -hf webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF:Q4_K_S --embeddings
- LM Studio
- Jan
- Ollama
How to use webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF with Ollama:
ollama run hf.co/webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF:Q4_K_S
- Unsloth Desktop
- Docker Model Runner
How to use webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF with Docker Model Runner:
docker model run hf.co/webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF:Q4_K_S
- Lemonade
How to use webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF:Q4_K_S
Run and chat with the model
lemonade run user.Sakura-EmbeddingGemma-2-AutoRound-GGUF-Q4_K_S
List all available models
lemonade list
- Atomic Chat
Download hq_benchmark_results.json from webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 36.2 kB
-
https://huggingface.co/webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF/resolve/main/hq_benchmark_results.json
- Command line
-
hf download hf://webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF/hq_benchmark_results.json
-
curl -L -o hq_benchmark_results.json https://huggingface.co/webmp3/Sakura-EmbeddingGemma-2-AutoRound-GGUF/resolve/main/hq_benchmark_results.json
36.2 kB
| { | |
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| "total_items": 300, | |
| "total_encoding_time_s": 22.847290992736816, | |
| "avg_latency_ms": 76.15763664245605, | |
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| }, | |
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| "method": "Same metrics and full document pool; queries grouped by existing lang field", | |
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| "retrieval": { | |
| "top1_agreement": 1.0, | |
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| } | |
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| "code_snippets_fidelity": { | |
| "mean_cosine": 0.9949401617050171, | |
| "median_cosine": 0.9952267408370972, | |
| "min_cosine": 0.9888275861740112, | |
| "mean_l2_drift": 0.09939484298229218, | |
| "spearman_rank_correlation": 0.9853363718246215 | |
| }, | |
| "text_retrieval": { | |
| "top1_agreement": 0.98, | |
| "top5_agreement": 0.87, | |
| "recall_at_1": 0.89, | |
| "recall_at_5": 1.0, | |
| "recall_at_10": 1.0, | |
| "ndcg_at_10": 0.9581580178688701 | |
| }, | |
| "code_retrieval": { | |
| "top1_agreement": 1.0, | |
| "top5_agreement": 0.8599999999999999, | |
| "recall_at_1": 0.98, | |
| "recall_at_5": 1.0, | |
| "recall_at_10": 1.0, | |
| "ndcg_at_10": 0.9665498988919873 | |
| } | |
| } | |
| } | |
| }, | |
| "runtime_smoke": { | |
| "server_load": "PASS", | |
| "llama_cpp_commit": "51ce9c11a6f2dfa895696c0048c4333e8953b728", | |
| "tests": [ | |
| { | |
| "text": "task: search result | query: mixed precision embeddings", | |
| "dimension": 768, | |
| "finite": true, | |
| "mrl": "PASS" | |
| }, | |
| { | |
| "text": "Ein deutscher Test f\u00fcr semantische Suche.", | |
| "dimension": 768, | |
| "finite": true, | |
| "mrl": "PASS" | |
| }, | |
| { | |
| "text": "def add(a, b): return a + b", | |
| "dimension": 768, | |
| "finite": true, | |
| "mrl": "PASS" | |
| } | |
| ], | |
| "status": "PASS" | |
| }, | |
| "ndcg_definition": "Reference-ranking graded nDCG@10; not independent human relevance judgments", | |
| "source_snapshot": "914f7f89142e33e77833254d9c9b90c3cef7303b", | |
| "runtime_flags": "--embedding --pooling mean -ngl 99 -c 2048 -b 2048 -ub 2048 --parallel 1", | |
| "published_unsloth_baseline": { | |
| "mean_cosine": 0.9934849143028259, | |
| "spearman": 0.9876057425348118, | |
| "text_top5": 0.896, | |
| "recall_at_5": 1.0 | |
| }, | |
| "bf16_reference_sha256": "f9e06dfc9a2395d7e7b948c78338e63f3b8c9f79a528ee5f8176f0d601f28a70" | |
| } |