Text Generation
Transformers
TensorBoard
Safetensors
English
qwen3
byte-level
pretraining
symbolic
text-generation-inference
Instructions to use dotlabs/void.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dotlabs/void.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="dotlabs/void.1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("dotlabs/void.1") model = AutoModelForCausalLM.from_pretrained("dotlabs/void.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use dotlabs/void.1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dotlabs/void.1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dotlabs/void.1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/dotlabs/void.1
- SGLang
How to use dotlabs/void.1 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "dotlabs/void.1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dotlabs/void.1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "dotlabs/void.1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dotlabs/void.1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use dotlabs/void.1 with Docker Model Runner:
docker model run hf.co/dotlabs/void.1
Update TensorBoard training metrics
Browse files
benchmark_cache/performance.json
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benchmark_cache/shard_scheduler.json
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| 68 |
-
"required_pages_per_second_upper_estimate": 0.
|
| 69 |
},
|
| 70 |
{
|
| 71 |
"source": "ultra_style",
|
| 72 |
"rows": 256,
|
| 73 |
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"tokens":
|
| 74 |
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"bytes":
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| 75 |
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"generation_seconds":
|
| 76 |
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"write_seconds": 0.
|
| 77 |
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"read_seconds": 0.
|
| 78 |
-
"tokens_per_second":
|
| 79 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 80 |
"estimated_pages_for_buffer": 1,
|
| 81 |
-
"required_token_positions_per_second":
|
| 82 |
-
"required_pages_per_second_upper_estimate": 0.
|
| 83 |
},
|
| 84 |
{
|
| 85 |
"source": "cortex",
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| 86 |
"rows": 128,
|
| 87 |
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"tokens":
|
| 88 |
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"bytes":
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| 89 |
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"generation_seconds": 0.
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| 90 |
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"write_seconds": 0.
|
| 91 |
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"read_seconds": 0.
|
| 92 |
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"tokens_per_second":
|
| 93 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 94 |
-
"estimated_pages_for_buffer":
|
| 95 |
-
"required_token_positions_per_second":
|
| 96 |
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"required_pages_per_second_upper_estimate": 0.
|
| 97 |
}
|
| 98 |
],
|
| 99 |
"gpu_measurement": "Selected forward/backward estimate; replaced by live successful update timings.",
|
|
@@ -108,462 +108,77 @@
|
|
| 108 |
"local_shard_size_benchmark": [
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| 109 |
{
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| 110 |
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| 111 |
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| 112 |
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| 114 |
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"read_seconds": 0.
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| 115 |
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"io_bytes_per_second":
|
| 116 |
"target_reached": true
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| 117 |
},
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| 118 |
{
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| 119 |
"target_mib": 32,
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| 120 |
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"actual_bytes":
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"read_seconds": 0.
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"io_bytes_per_second":
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| 125 |
"target_reached": false
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| 126 |
},
|
| 127 |
{
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| 128 |
"target_mib": 64,
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| 129 |
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"actual_bytes":
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| 130 |
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"pages":
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| 132 |
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"read_seconds": 0.
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| 133 |
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"io_bytes_per_second":
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| 134 |
"target_reached": false
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| 135 |
},
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| 136 |
{
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| 137 |
"target_mib": 128,
|
| 138 |
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"actual_bytes":
|
| 139 |
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"pages":
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"packing_seconds": 0.
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| 141 |
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"read_seconds": 0.
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| 142 |
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"io_bytes_per_second":
|
| 143 |
"target_reached": false
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| 144 |
},
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| 145 |
{
|
| 146 |
"target_mib": 256,
|
| 147 |
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"actual_bytes":
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| 148 |
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"pages":
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| 150 |
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"read_seconds": 0.
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| 151 |
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"io_bytes_per_second":
|
| 152 |
"target_reached": false
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| 153 |
}
|
| 154 |
],
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| 155 |
"shard_benchmark_scope": "Local packing/read measurements; upload capacity measured only on real data commits. Targets larger than available pages are sample-limited.",
|
| 156 |
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"estimated_fresh_generation_batch_seconds":
|
| 157 |
"selected": {
|
| 158 |
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"prefetch_batches":
|
| 159 |
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|
| 160 |
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"batch_memory_estimate_bytes":
|
| 161 |
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"producer_batch_seconds":
|
| 162 |
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"producer_p95_seconds":
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| 163 |
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| 164 |
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|
| 165 |
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"gpu_batches_per_second": 1.
|
| 166 |
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"producer_headroom":
|
| 167 |
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"sustainable":
|
| 168 |
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"buffer_seconds": 60.
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| 169 |
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"buffer_drain_seconds":
|
| 170 |
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| 171 |
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"upload_pages_per_commit":
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| 172 |
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"max_pending_pages":
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| 173 |
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"generation_bytes_per_second":
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| 174 |
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"upload_bytes_per_second":
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| 175 |
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"upload_sustainable":
|
| 176 |
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| 177 |
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| 178 |
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"estimated_full_shards_per_hour":
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| 179 |
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|
| 180 |
},
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| 181 |
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"upload_measurements": [
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{
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| 517 |
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},
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| 518 |
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{
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| 519 |
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| 523 |
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},
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{
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| 525 |
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| 526 |
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|
| 527 |
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| 528 |
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| 529 |
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},
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{
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| 531 |
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"seconds": 1.1678855200007092,
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| 532 |
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| 534 |
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| 535 |
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},
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{
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| 538 |
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| 540 |
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| 541 |
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| 547 |
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{
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| 549 |
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| 565 |
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| 566 |
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],
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| 567 |
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| 568 |
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| 569 |
"kind": "data",
|
|
@@ -602,11 +217,7 @@
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|
| 602 |
"source": "f8722b66ff2f92bca174f36564336149e85c65c48b964d05ff3a4d5d85da308f",
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| 603 |
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| 606 |
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| 608 |
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| 609 |
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| 610 |
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| 611 |
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| 612 |
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| 1 |
{
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| 2 |
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| 3 |
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| 4 |
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| 11 |
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| 12 |
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| 13 |
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{
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| 15 |
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| 16 |
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| 22 |
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| 23 |
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| 24 |
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| 27 |
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| 28 |
{
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| 29 |
"source": "rewrite6",
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| 30 |
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| 32 |
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| 36 |
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| 37 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
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| 38 |
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| 39 |
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| 41 |
},
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| 42 |
{
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| 43 |
"source": "openmath",
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| 44 |
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| 50 |
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| 51 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
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| 52 |
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| 56 |
{
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"source": "ultra_qa",
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"note": "Bounded fresh sample; full-page latency is an extrapolation.",
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{
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| 83 |
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{
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],
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| 99 |
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| 108 |
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| 109 |
{
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| 110 |
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{
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| 126 |
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| 127 |
{
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| 128 |
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{
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{
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| 153 |
}
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| 154 |
],
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| 155 |
"shard_benchmark_scope": "Local packing/read measurements; upload capacity measured only on real data commits. Targets larger than available pages are sample-limited.",
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| 156 |
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"selection_policy": "Smallest shard within 90% of measured local peak, enlarged to amortize 30 seconds of measured page production; bounded to 256 MiB."
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| 180 |
},
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"upload_measurements": [],
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| 182 |
"cache_key": {
|
| 183 |
"version": 1,
|
| 184 |
"kind": "data",
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| 217 |
"source": "f8722b66ff2f92bca174f36564336149e85c65c48b964d05ff3a4d5d85da308f",
|
| 218 |
"cpu": "unknown",
|
| 219 |
"cpu_count": 20,
|
| 220 |
+
"microbatch": 90
|
| 221 |
},
|
| 222 |
+
"cache_reused": false
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| 223 |
}
|
runs/void-byte-v1/events.out.tfevents.1790824801.afc92292-ba09-4e51-8d82-bc1983323308-sdcdh.469.0.1790824801708454555-41033672
ADDED
|
@@ -0,0 +1,3 @@
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:24f5c75d5a7fd13da224df91bf8ca10f057a9d45bb13ecc04c67f1bbf3650a54
|
| 3 |
+
size 165
|