prithivMLmods/Gender-Classifier-Mini
prithivMLmods/Gender-Classifier-Mini
Parameters
366.5M
Context
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Downloads
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Likes
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Architecture
siglip
12 layers · head 64 · hidden 768
GPU Requirements
VRAM / RAM / disk estimates by quantization and usage scenario
| Quantization | Minimum | Recommended | Production |
|---|---|---|---|
| FP1616bit | 3.2 GB RAM 32.0 · Disk 40.1 | 3.6 GB RAM 32.0 · Disk 66.1 | 5.8 GB RAM 32.0 · Disk 105.1 |
| FP88bit | 2.8 GB RAM 32.0 · Disk 39.5 | 3.1 GB RAM 32.0 · Disk 65.5 | 5.4 GB RAM 32.0 · Disk 104.5 |
| INT88bit | 2.8 GB RAM 32.0 · Disk 39.5 | 3.1 GB RAM 32.0 · Disk 65.5 | 5.4 GB RAM 32.0 · Disk 104.5 |
| AWQ4bit | 2.6 GB RAM 32.0 · Disk 39.3 | 2.9 GB RAM 32.0 · Disk 65.3 | 5.1 GB RAM 32.0 · Disk 104.3 |
| GPTQ4bit | 2.6 GB RAM 32.0 · Disk 39.3 | 2.9 GB RAM 32.0 · Disk 65.3 | 5.1 GB RAM 32.0 · Disk 104.3 |
| GGUF4bit | 2.6 GB RAM 32.0 · Disk 39.3 | 2.9 GB RAM 32.0 · Disk 65.3 | 5.1 GB RAM 32.0 · Disk 104.3 |
GPU Recommendations
1× RTX 3080 Ti
12 GB VRAM
≈ 5066.7 tok/s
Effective production throughput ≈ 3546.7 tok/s
score 0.5595
1× Tesla V100
16 GB VRAM
≈ 0 tok/s (N/A — benchmark unavailable)
Effective production throughput ≈ 0 tok/s
score 0.5378
8× RTX 5080
128 GB VRAM
≈ 17066.7 tok/s
Effective production throughput ≈ 11946.7 tok/s
score 0.3607
1× RTX 4060 Ti
8 GB VRAM
≈ 1600 tok/s
Effective production throughput ≈ 1120 tok/s
score 0.588
💬 Community — real deployment experience
0 Articles · 0 Benchmarks
GPUs that fit (single card)
Tesla V100
16 GB VRAM
$35.7
/mo · vast
RTX 4060 Ti
8 GB VRAM
$49.6
/mo · vast
RTX 3080
10 GB VRAM
$64.3
/mo · vast
RTX 4070S Ti
16 GB VRAM
$68.5
/mo · vast
L4
24 GB VRAM
$76.2
/mo · vast