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
Qwen90M step 400000; complete resumable checkpoint
Browse files- complete.json +7 -7
- coverage.json +46 -46
- latest.json +1 -1
- model.safetensors +1 -1
- performance.json +66 -67
- shard_scheduler.json +169 -413
- trainer.pt +2 -2
- training_config.json +4 -4
complete.json
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coverage.json
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latest.json
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model.safetensors
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performance.json
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|
| 101 |
-
"estimated_update_seconds": 1.
|
| 102 |
-
"input_tokens_per_second":
|
| 103 |
},
|
| 104 |
{
|
| 105 |
"microbatch": 16,
|
| 106 |
"mode": "compiled",
|
| 107 |
-
"microbatch_seconds": 0.
|
| 108 |
-
"peak_gb": 16.
|
| 109 |
"fits_budget": true,
|
| 110 |
-
"estimated_update_seconds": 0.
|
| 111 |
-
"input_tokens_per_second":
|
| 112 |
},
|
| 113 |
{
|
| 114 |
"microbatch": 32,
|
| 115 |
"mode": "compiled",
|
| 116 |
-
"microbatch_seconds": 0.
|
| 117 |
-
"peak_gb":
|
| 118 |
"fits_budget": true,
|
| 119 |
-
"estimated_update_seconds": 0.
|
| 120 |
-
"input_tokens_per_second":
|
| 121 |
},
|
| 122 |
{
|
| 123 |
"microbatch": 48,
|
| 124 |
"mode": "compiled",
|
| 125 |
-
"microbatch_seconds": 0.
|
| 126 |
-
"peak_gb":
|
| 127 |
"fits_budget": true,
|
| 128 |
-
"estimated_update_seconds": 0.
|
| 129 |
-
"input_tokens_per_second":
|
| 130 |
},
|
| 131 |
{
|
| 132 |
"microbatch": 64,
|
| 133 |
"mode": "compiled",
|
| 134 |
-
"microbatch_seconds": 0.
|
| 135 |
-
"peak_gb": 63.
|
| 136 |
"fits_budget": true,
|
| 137 |
-
"estimated_update_seconds": 0.
|
| 138 |
-
"input_tokens_per_second":
|
| 139 |
},
|
| 140 |
{
|
| 141 |
"microbatch": 72,
|
| 142 |
"mode": "compiled",
|
| 143 |
-
"microbatch_seconds": 0.
|
| 144 |
-
"peak_gb":
|
| 145 |
"fits_budget": true,
|
| 146 |
-
"estimated_update_seconds": 0.
|
| 147 |
-
"input_tokens_per_second":
|
| 148 |
},
|
| 149 |
{
|
| 150 |
"microbatch": 76,
|
| 151 |
"mode": "compiled",
|
| 152 |
-
"microbatch_seconds": 0.
|
| 153 |
-
"peak_gb":
|
| 154 |
"fits_budget": true,
|
| 155 |
-
"estimated_update_seconds": 0.
|
| 156 |
-
"input_tokens_per_second":
|
| 157 |
},
|
| 158 |
{
|
| 159 |
"microbatch": 80,
|
| 160 |
"mode": "compiled",
|
| 161 |
-
"microbatch_seconds": 0.
|
| 162 |
-
"peak_gb":
|
| 163 |
"fits_budget": true,
|
| 164 |
-
"estimated_update_seconds": 0.
|
| 165 |
-
"input_tokens_per_second":
|
| 166 |
},
|
| 167 |
{
|
| 168 |
"microbatch": 86,
|
| 169 |
"mode": "compiled",
|
| 170 |
-
"microbatch_seconds": 0.
|
| 171 |
-
"peak_gb":
|
| 172 |
"fits_budget": true,
|
| 173 |
-
"estimated_update_seconds": 0.
|
| 174 |
-
"input_tokens_per_second":
|
| 175 |
},
|
| 176 |
{
|
| 177 |
"microbatch": 90,
|
| 178 |
"mode": "compiled",
|
| 179 |
-
"microbatch_seconds": 0.
|
| 180 |
-
"peak_gb":
|
| 181 |
-
"fits_budget":
|
| 182 |
-
"estimated_update_seconds": 0.
|
| 183 |
-
"input_tokens_per_second":
|
| 184 |
}
|
| 185 |
],
|
| 186 |
"failures": [
|
|
@@ -216,8 +216,7 @@
|
|
| 216 |
}
|
| 217 |
],
|
| 218 |
"selection_policy": "max_batch",
|
| 219 |
-
"budget_gb":
|
| 220 |
"reserve_gb": 2.1791439056396484,
|
| 221 |
-
"note": "Forward/backward throughput; excludes optimizer, data, logging and checkpoint time."
|
| 222 |
-
"legacy_seed_verified": false
|
| 223 |
}
|
|
|
|
| 39 |
"compile_model": true,
|
| 40 |
"autotune_microbatch": true,
|
| 41 |
"attention_backend": "flash",
|
| 42 |
+
"vram_fraction": 0.98
|
| 43 |
},
|
| 44 |
"source": "e6d135a4487a9fd1907e12903cda79e75fd61305fad149fda7ec5281279dc18b",
|
| 45 |
"requested_microbatch_ceiling": 90
|
| 46 |
},
|
| 47 |
+
"cache_reused": false,
|
| 48 |
"attention": "PyTorch FlashAttention (forced; forward/backward verified)",
|
| 49 |
"selected": {
|
| 50 |
+
"microbatch": 90,
|
| 51 |
"mode": "compiled",
|
| 52 |
+
"microbatch_seconds": 0.9302335780000135,
|
| 53 |
+
"peak_gb": 89.3772840499878,
|
| 54 |
"fits_budget": true,
|
| 55 |
+
"estimated_update_seconds": 0.9302335780000135,
|
| 56 |
+
"input_tokens_per_second": 198143.7827650609
|
| 57 |
},
|
| 58 |
"measurements": [
|
| 59 |
{
|
| 60 |
"microbatch": 8,
|
| 61 |
"mode": "eager",
|
| 62 |
+
"microbatch_seconds": 0.15844926500000156,
|
| 63 |
+
"peak_gb": 14.764304637908936,
|
| 64 |
"fits_budget": true,
|
| 65 |
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"estimated_update_seconds": 1.8007989265000077,
|
| 66 |
+
"input_tokens_per_second": 103402.18365796673
|
| 67 |
},
|
| 68 |
{
|
| 69 |
"microbatch": 16,
|
| 70 |
"mode": "eager",
|
| 71 |
+
"microbatch_seconds": 0.34631374599999276,
|
| 72 |
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"peak_gb": 28.084960460662842,
|
| 73 |
"fits_budget": true,
|
| 74 |
+
"estimated_update_seconds": 1.929804849999968,
|
| 75 |
+
"input_tokens_per_second": 94619.40329680326
|
| 76 |
},
|
| 77 |
{
|
| 78 |
"microbatch": 32,
|
| 79 |
"mode": "eager",
|
| 80 |
+
"microbatch_seconds": 0.7831460159999892,
|
| 81 |
+
"peak_gb": 54.827155113220215,
|
| 82 |
"fits_budget": true,
|
| 83 |
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"estimated_update_seconds": 2.188403235499976,
|
| 84 |
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"input_tokens_per_second": 83682.98971210101
|
| 85 |
},
|
| 86 |
{
|
| 87 |
"microbatch": 48,
|
| 88 |
"mode": "eager",
|
| 89 |
+
"microbatch_seconds": 1.1706683780000162,
|
| 90 |
+
"peak_gb": 81.63183498382568,
|
| 91 |
"fits_budget": true,
|
| 92 |
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"estimated_update_seconds": 2.1949380675000043,
|
| 93 |
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"input_tokens_per_second": 83972.54239321277
|
| 94 |
},
|
| 95 |
{
|
| 96 |
"microbatch": 8,
|
| 97 |
"mode": "compiled",
|
| 98 |
+
"microbatch_seconds": 0.08827481200000875,
|
| 99 |
+
"peak_gb": 9.113307476043701,
|
| 100 |
"fits_budget": true,
|
| 101 |
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"estimated_update_seconds": 1.008851873500106,
|
| 102 |
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"input_tokens_per_second": 185602.20779624404
|
| 103 |
},
|
| 104 |
{
|
| 105 |
"microbatch": 16,
|
| 106 |
"mode": "compiled",
|
| 107 |
+
"microbatch_seconds": 0.17047579999996287,
|
| 108 |
+
"peak_gb": 16.87287473678589,
|
| 109 |
"fits_budget": true,
|
| 110 |
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"estimated_update_seconds": 0.9571819019997747,
|
| 111 |
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"input_tokens_per_second": 192214.96540862185
|
| 112 |
},
|
| 113 |
{
|
| 114 |
"microbatch": 32,
|
| 115 |
"mode": "compiled",
|
| 116 |
+
"microbatch_seconds": 0.34263174000000163,
|
| 117 |
+
"peak_gb": 32.49641752243042,
|
| 118 |
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|
| 119 |
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"estimated_update_seconds": 0.9525396829999977,
|
| 120 |
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"input_tokens_per_second": 191272.41393339593
|
| 121 |
},
|
| 122 |
{
|
| 123 |
"microbatch": 48,
|
| 124 |
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|
| 125 |
+
"microbatch_seconds": 0.5075005140000144,
|
| 126 |
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|
| 127 |
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|
| 128 |
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|
| 129 |
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"input_tokens_per_second": 193702.2668709991
|
| 130 |
},
|
| 131 |
{
|
| 132 |
"microbatch": 64,
|
| 133 |
"mode": "compiled",
|
| 134 |
+
"microbatch_seconds": 0.6643874849999634,
|
| 135 |
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"peak_gb": 63.757601737976074,
|
| 136 |
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|
| 137 |
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|
| 138 |
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"input_tokens_per_second": 197282.46386219515
|
| 139 |
},
|
| 140 |
{
|
| 141 |
"microbatch": 72,
|
| 142 |
"mode": "compiled",
|
| 143 |
+
"microbatch_seconds": 0.7446585950000326,
|
| 144 |
+
"peak_gb": 71.65071392059326,
|
| 145 |
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|
| 146 |
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|
| 147 |
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"input_tokens_per_second": 198018.26097232322
|
| 148 |
},
|
| 149 |
{
|
| 150 |
"microbatch": 76,
|
| 151 |
"mode": "compiled",
|
| 152 |
+
"microbatch_seconds": 0.7858128550000174,
|
| 153 |
+
"peak_gb": 75.5242338180542,
|
| 154 |
"fits_budget": true,
|
| 155 |
+
"estimated_update_seconds": 0.9300540555000225,
|
| 156 |
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"input_tokens_per_second": 198072.60597689834
|
| 157 |
},
|
| 158 |
{
|
| 159 |
"microbatch": 80,
|
| 160 |
"mode": "compiled",
|
| 161 |
+
"microbatch_seconds": 0.8269688110000288,
|
| 162 |
+
"peak_gb": 79.40062236785889,
|
| 163 |
"fits_budget": true,
|
| 164 |
+
"estimated_update_seconds": 0.9293605420000404,
|
| 165 |
+
"input_tokens_per_second": 198121.13567121493
|
| 166 |
},
|
| 167 |
{
|
| 168 |
"microbatch": 86,
|
| 169 |
"mode": "compiled",
|
| 170 |
+
"microbatch_seconds": 0.8882591199999865,
|
| 171 |
+
"peak_gb": 85.4687147140503,
|
| 172 |
"fits_budget": true,
|
| 173 |
+
"estimated_update_seconds": 0.9413692904999778,
|
| 174 |
+
"input_tokens_per_second": 198284.4825730612
|
| 175 |
},
|
| 176 |
{
|
| 177 |
"microbatch": 90,
|
| 178 |
"mode": "compiled",
|
| 179 |
+
"microbatch_seconds": 0.9302335780000135,
|
| 180 |
+
"peak_gb": 89.3772840499878,
|
| 181 |
+
"fits_budget": true,
|
| 182 |
+
"estimated_update_seconds": 0.9302335780000135,
|
| 183 |
+
"input_tokens_per_second": 198143.7827650609
|
| 184 |
}
|
| 185 |
],
|
| 186 |
"failures": [
|
|
|
|
| 216 |
}
|
| 217 |
],
|
| 218 |
"selection_policy": "max_batch",
|
| 219 |
+
"budget_gb": 92.52170804977416,
|
| 220 |
"reserve_gb": 2.1791439056396484,
|
| 221 |
+
"note": "Forward/backward throughput; excludes optimizer, data, logging and checkpoint time."
|
|
|
|
| 222 |
}
|
shard_scheduler.json
CHANGED
|
@@ -1,99 +1,99 @@
|
|
| 1 |
{
|
| 2 |
"version": 1,
|
| 3 |
"startup_batch_seconds": [
|
| 4 |
-
|
| 5 |
-
0.
|
| 6 |
-
0.
|
| 7 |
-
0.
|
| 8 |
-
0.
|
| 9 |
-
0.
|
| 10 |
-
0.
|
| 11 |
-
0.
|
| 12 |
],
|
| 13 |
"source_benchmarks": [
|
| 14 |
{
|
| 15 |
"source": "climbmix",
|
| 16 |
"rows": 256,
|
| 17 |
-
"tokens":
|
| 18 |
-
"bytes":
|
| 19 |
-
"generation_seconds":
|
| 20 |
-
"write_seconds": 0.
|
| 21 |
-
"read_seconds": 0.
|
| 22 |
-
"tokens_per_second":
|
| 23 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 24 |
"estimated_pages_for_buffer": 1,
|
| 25 |
-
"required_token_positions_per_second":
|
| 26 |
-
"required_pages_per_second_upper_estimate": 0.
|
| 27 |
},
|
| 28 |
{
|
| 29 |
"source": "rewrite6",
|
| 30 |
"rows": 256,
|
| 31 |
-
"tokens":
|
| 32 |
-
"bytes":
|
| 33 |
-
"generation_seconds":
|
| 34 |
-
"write_seconds": 0.
|
| 35 |
-
"read_seconds": 0.
|
| 36 |
-
"tokens_per_second":
|
| 37 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 38 |
"estimated_pages_for_buffer": 1,
|
| 39 |
-
"required_token_positions_per_second":
|
| 40 |
-
"required_pages_per_second_upper_estimate": 0.
|
| 41 |
},
|
| 42 |
{
|
| 43 |
"source": "openmath",
|
| 44 |
"rows": 256,
|
| 45 |
-
"tokens":
|
| 46 |
-
"bytes":
|
| 47 |
-
"generation_seconds": 0.
|
| 48 |
-
"write_seconds": 0.
|
| 49 |
-
"read_seconds": 0.
|
| 50 |
-
"tokens_per_second":
|
| 51 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 52 |
"estimated_pages_for_buffer": 1,
|
| 53 |
-
"required_token_positions_per_second":
|
| 54 |
-
"required_pages_per_second_upper_estimate": 0.
|
| 55 |
},
|
| 56 |
{
|
| 57 |
"source": "ultra_qa",
|
| 58 |
"rows": 256,
|
| 59 |
-
"tokens":
|
| 60 |
-
"bytes":
|
| 61 |
-
"generation_seconds":
|
| 62 |
-
"write_seconds": 0.
|
| 63 |
-
"read_seconds": 0.
|
| 64 |
-
"tokens_per_second":
|
| 65 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 66 |
"estimated_pages_for_buffer": 1,
|
| 67 |
-
"required_token_positions_per_second":
|
| 68 |
-
"required_pages_per_second_upper_estimate": 0.
|
| 69 |
},
|
| 70 |
{
|
| 71 |
"source": "ultra_style",
|
| 72 |
"rows": 256,
|
| 73 |
-
"tokens":
|
| 74 |
-
"bytes":
|
| 75 |
-
"generation_seconds":
|
| 76 |
-
"write_seconds": 0.
|
| 77 |
-
"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",
|
| 86 |
"rows": 128,
|
| 87 |
-
"tokens":
|
| 88 |
-
"bytes":
|
| 89 |
-
"generation_seconds": 0.
|
| 90 |
-
"write_seconds": 0.
|
| 91 |
-
"read_seconds": 0.
|
| 92 |
-
"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 |
-
"required_pages_per_second_upper_estimate": 0.
|
| 97 |
}
|
| 98 |
],
|
| 99 |
"gpu_measurement": "Selected forward/backward estimate; replaced by live successful update timings.",
|
|
@@ -108,460 +108,220 @@
|
|
| 108 |
"local_shard_size_benchmark": [
|
| 109 |
{
|
| 110 |
"target_mib": 16,
|
| 111 |
-
"actual_bytes":
|
| 112 |
-
"pages":
|
| 113 |
-
"packing_seconds": 0.
|
| 114 |
-
"read_seconds": 0.
|
| 115 |
-
"io_bytes_per_second":
|
| 116 |
"target_reached": true
|
| 117 |
},
|
| 118 |
{
|
| 119 |
"target_mib": 32,
|
| 120 |
-
"actual_bytes":
|
| 121 |
-
"pages":
|
| 122 |
-
"packing_seconds": 0.
|
| 123 |
-
"read_seconds": 0.
|
| 124 |
-
"io_bytes_per_second":
|
| 125 |
"target_reached": false
|
| 126 |
},
|
| 127 |
{
|
| 128 |
"target_mib": 64,
|
| 129 |
-
"actual_bytes":
|
| 130 |
-
"pages":
|
| 131 |
-
"packing_seconds": 0.
|
| 132 |
-
"read_seconds": 0.
|
| 133 |
-
"io_bytes_per_second":
|
| 134 |
"target_reached": false
|
| 135 |
},
|
| 136 |
{
|
| 137 |
"target_mib": 128,
|
| 138 |
-
"actual_bytes":
|
| 139 |
-
"pages":
|
| 140 |
-
"packing_seconds": 0.
|
| 141 |
-
"read_seconds": 0.
|
| 142 |
-
"io_bytes_per_second":
|
| 143 |
"target_reached": false
|
| 144 |
},
|
| 145 |
{
|
| 146 |
"target_mib": 256,
|
| 147 |
-
"actual_bytes":
|
| 148 |
-
"pages":
|
| 149 |
-
"packing_seconds": 0.
|
| 150 |
-
"read_seconds": 0.
|
| 151 |
-
"io_bytes_per_second":
|
| 152 |
"target_reached": false
|
| 153 |
}
|
| 154 |
],
|
| 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 |
-
"estimated_fresh_generation_batch_seconds":
|
| 157 |
"selected": {
|
| 158 |
-
"prefetch_batches":
|
| 159 |
"prefetch_capacity_limit": 512,
|
| 160 |
-
"batch_memory_estimate_bytes":
|
| 161 |
-
"producer_batch_seconds": 0.
|
| 162 |
-
"producer_p95_seconds": 0.
|
| 163 |
-
"gpu_update_seconds": 0.
|
| 164 |
-
"producer_batches_per_second":
|
| 165 |
-
"gpu_batches_per_second": 1.
|
| 166 |
-
"producer_headroom":
|
| 167 |
"sustainable": true,
|
| 168 |
-
"buffer_seconds": 60.
|
| 169 |
"buffer_drain_seconds": null,
|
| 170 |
"shard_target_mib": 16,
|
| 171 |
-
"upload_pages_per_commit":
|
| 172 |
"max_pending_pages": 4096,
|
| 173 |
-
"generation_bytes_per_second":
|
| 174 |
-
"upload_bytes_per_second":
|
| 175 |
"upload_sustainable": true,
|
| 176 |
"logical_page_rows": 4096,
|
| 177 |
"logical_cortex_page_rows": 128,
|
| 178 |
-
"estimated_full_shards_per_hour":
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trainer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
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oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
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oid sha256:0883783165f69503eba3b62bf8c9c7a6e664527b2bcaeee310413d02bf169eb3
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| 3 |
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size 721779455
|
training_config.json
CHANGED
|
@@ -4,7 +4,7 @@
|
|
| 4 |
"run_name": "void-byte-v1",
|
| 5 |
"context": 2048,
|
| 6 |
"global_batch": 90,
|
| 7 |
-
"micro_batch":
|
| 8 |
"microbatch_candidates": [
|
| 9 |
8,
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| 10 |
16,
|
|
@@ -46,8 +46,8 @@
|
|
| 46 |
"cpu_threads": 4,
|
| 47 |
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|
| 48 |
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|
| 49 |
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|
| 50 |
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|
| 51 |
"memory_pages": 12,
|
| 52 |
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|
| 53 |
"force_rebenchmark": false,
|
|
@@ -66,7 +66,7 @@
|
|
| 66 |
"benchmark_compile": true,
|
| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
"work_dir": "/marimo/qwen90m_workspace/runs/void-byte-v1",
|
|
|
|
| 4 |
"run_name": "void-byte-v1",
|
| 5 |
"context": 2048,
|
| 6 |
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|
| 7 |
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"micro_batch": 90,
|
| 8 |
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|
| 9 |
8,
|
| 10 |
16,
|
|
|
|
| 46 |
"cpu_threads": 4,
|
| 47 |
"page_rows": 4096,
|
| 48 |
"cortex_page_rows": 128,
|
| 49 |
+
"prefetch_batches": 63,
|
| 50 |
+
"prefetch_low_water": 31,
|
| 51 |
"memory_pages": 12,
|
| 52 |
"cache_gb": 20,
|
| 53 |
"force_rebenchmark": false,
|
|
|
|
| 66 |
"benchmark_compile": true,
|
| 67 |
"autotune_microbatch": true,
|
| 68 |
"attention_backend": "flash",
|
| 69 |
+
"vram_fraction": 0.98,
|
| 70 |
"upload": true,
|
| 71 |
"hub_resume": true,
|
| 72 |
"work_dir": "/marimo/qwen90m_workspace/runs/void-byte-v1",
|