Text Generation
GGUF
MambaSSM
English
ruvltra
sona
adaptive-learning
quantized
edge-device
embedded
iot
turboquant
kv-cache-compression
flash-attention
speculative-decoding
graph-rag
hybrid-search
vector-database
ruvector
diskann
colbert
imatrix
conversational
Instructions to use ruv/ruvltra-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MambaSSM
How to use ruv/ruvltra-small with MambaSSM:
from mamba_ssm import MambaLMHeadModel model = MambaLMHeadModel.from_pretrained("ruv/ruvltra-small") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ruv/ruvltra-small with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf ruv/ruvltra-small:Q4_K_M # Run inference directly in the terminal: llama cli -hf ruv/ruvltra-small:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ruv/ruvltra-small:Q4_K_M # Run inference directly in the terminal: llama cli -hf ruv/ruvltra-small:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf ruv/ruvltra-small:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf ruv/ruvltra-small:Q4_K_M
Use Docker
docker model run hf.co/ruv/ruvltra-small:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use ruv/ruvltra-small with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ruv/ruvltra-small" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ruv/ruvltra-small", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ruv/ruvltra-small:Q4_K_M
- Ollama
How to use ruv/ruvltra-small with Ollama:
ollama run hf.co/ruv/ruvltra-small:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use ruv/ruvltra-small with Docker Model Runner:
docker model run hf.co/ruv/ruvltra-small:Q4_K_M
- Lemonade
How to use ruv/ruvltra-small with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ruv/ruvltra-small:Q4_K_M
Run and chat with the model
lemonade run user.ruvltra-small-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Commit History
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Add L4 GPU benchmark results (75.4 tok/s)
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Calibration: benchmark_results.json
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Calibration: default.turboquant.json
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Calibration: benchmark_results.json
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Calibration: default.turboquant.json
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Calibration: benchmark_results.json
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Calibration: default.turboquant.json
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Add default TurboQuant KV-cache profile (ADR-129)
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Add TurboQuant compatibility, v2.1.0 ecosystem tags
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Add TurboQuant compatibility and v2.1.0 ecosystem tags
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Enhanced model card with badges, tutorials, and documentation
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Add model card
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Upload tokenizer
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Upload RuvLTRA 0.5B Q4_K_M model
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initial commit
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