dbmdz/bert-large-cased-finetuned-conll03-english
dbmdz/bert-large-cased-finetuned-conll03-english
Parameters
331.7M
Context
512
Downloads
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Likes
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Architecture
bert
24 layers · head 64 · hidden 1024
GPU Requirements
VRAM / RAM / disk estimates by quantization and usage scenario
| Quantization | Minimum | Recommended | Production |
|---|---|---|---|
| FP1616bit | 3.6 GB RAM 32.0 · Disk 40.0 | 8.3 GB RAM 32.0 · Disk 66.0 | 39.3 GB RAM 58.9 · Disk 105.0 |
| FP88bit | 3.2 GB RAM 32.0 · Disk 39.5 | 7.9 GB RAM 32.0 · Disk 65.5 | 38.8 GB RAM 58.2 · Disk 104.5 |
| INT88bit | 3.2 GB RAM 32.0 · Disk 39.5 | 7.9 GB RAM 32.0 · Disk 65.5 | 38.8 GB RAM 58.2 · Disk 104.5 |
| AWQ4bit | 3.0 GB RAM 32.0 · Disk 39.3 | 7.7 GB RAM 32.0 · Disk 65.3 | 38.6 GB RAM 57.9 · Disk 104.3 |
| GPTQ4bit | 3.0 GB RAM 32.0 · Disk 39.3 | 7.7 GB RAM 32.0 · Disk 65.3 | 38.6 GB RAM 57.9 · Disk 104.3 |
| GGUF4bit | 3.0 GB RAM 32.0 · Disk 39.3 | 7.7 GB RAM 32.0 · Disk 65.3 | 38.6 GB RAM 57.9 · Disk 104.3 |
GPU Recommendations
1× RTX 3080 Ti
12 GB VRAM
≈ 5700 tok/s
Effective production throughput ≈ 3990 tok/s
score 0.6662
1× Tesla V100
16 GB VRAM
≈ 0 tok/s (N/A — benchmark unavailable)
Effective production throughput ≈ 0 tok/s
score 0.6174
8× H200 SXM
1128 GB VRAM
≈ 96000 tok/s
Effective production throughput ≈ 67200 tok/s
score 0.2197
1× RTX 4060 Ti
8 GB VRAM
≈ 1800 tok/s
Effective production throughput ≈ 1260 tok/s
score 0.6375
💬 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
$59.2
/mo · vast
RTX 3080 Ti
12 GB VRAM
$60.0
/mo · vast
RTX 3080
10 GB VRAM
$63.8
/mo · vast
RTX 4070S Ti
16 GB VRAM
$68.5
/mo · vast