Instructions to use mlx-works/Ornith-1.0-35B-oQ2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-works/Ornith-1.0-35B-oQ2 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Ornith-1.0-35B-oQ2 mlx-works/Ornith-1.0-35B-oQ2
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
Upload README.md with huggingface_hub
Browse files
README.md
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- mlx
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- quantized
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---
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# Ornith-1.0-35B-oQ2
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This model was quantized using [oQ](https://github.com/jundot/omlx) (oMLX v0.5.
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## Quantization details
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- **Bits**: 2
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- **Group size**: 64
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- **Format**: MLX safetensors
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- mlx
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- oq
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- benchmark
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- performance
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- moe
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- ornith
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---
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# Ornith-1.0-35B-oQ2
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This model was quantized using [oQ](https://github.com/jundot/omlx) (oMLX v0.5.3) mixed-precision quantization.
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Base model: [Ornith-1.0-35B](https://huggingface.co/Ornith-1.0-35B)
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## Quantization details
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- **Bits**: 2
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- **Group size**: 64
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- **Format**: MLX safetensors
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## Environment
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- **Hardware**: M5 MacBook Air 32GB
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- **Inference Framework**: oMLX v0.5.3
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- **Max Concurrent Requests**: 4
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- **Settings**:
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- Thinking: Disabled
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- TurboQuant KV Cache: Enabled
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## Performance Benchmarks
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> **Note**: Results are for reference only and may vary depending on hardware, software configuration, and workload.
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### Single Request Results
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| Test | TTFT(ms) | TPOT(ms) | pp TPS | tg TPS | E2E(s) | Throughput | Peak Mem |
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|------|----------|----------|--------|--------|--------|------------|----------|
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| pp1024/tg128 | 1063.3 | 20.83 | 963.0 tok/s | 48.4 tok/s | 3.722 | 309.5 tok/s | 12.62 GB |
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| pp4096/tg128 | 3662.7 | 21.71 | 1118.3 tok/s | 46.4 tok/s | 6.435 | 656.4 tok/s | 13.36 GB |
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### Continuous Batching (pp1024 / tg128)
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| Batch | tg TPS | Speedup | pp TPS | pp TPS/req | TTFT(ms) | E2E(s) |
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|-------|--------|---------|--------|------------|----------|--------|
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| 1x | 48.4 tok/s | 1.00x | 963.0 tok/s | 963.0 tok/s | 1063.3 | 3.722 |
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| 2x | 67.2 tok/s | 1.39x | 871.7 tok/s | 435.9 tok/s | 2349.2 | 6.159 |
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| 4x | 100.6 tok/s | 2.08x | 868.4 tok/s | 217.1 tok/s | 4569.1 | 9.804 |
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## Intelligence Benchmark
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> **Note**: Each benchmark round tests only 30 questions. Results are for reference only.
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| Benchmark | Accuracy | Correct | Total | Time(s) | Think |
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|-----------|----------|---------|-------|---------|-------|
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| MMLU | 70.0% | 21 | 30 | 33 | No |
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| TRUTHFULQA | 76.7% | 23 | 30 | 15.3 | No |
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| GSM8K | 96.7% | 29 | 30 | 100.3 | No |
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| MATHQA | 16.7% | 5 | 30 | 69.6 | No |
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| HUMANEVAL | 83.3% | 25 | 30 | 172.8 | No |
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