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/shard_scheduler.json
CHANGED
|
@@ -22,8 +22,8 @@
|
|
| 22 |
"tokens_per_second": 1062967.6168812835,
|
| 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",
|
|
@@ -36,8 +36,8 @@
|
|
| 36 |
"tokens_per_second": 1206672.263377472,
|
| 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",
|
|
@@ -50,8 +50,8 @@
|
|
| 50 |
"tokens_per_second": 410042.7581134458,
|
| 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",
|
|
@@ -64,8 +64,8 @@
|
|
| 64 |
"tokens_per_second": 2163486.5624068812,
|
| 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",
|
|
@@ -78,8 +78,8 @@
|
|
| 78 |
"tokens_per_second": 1546694.2737633225,
|
| 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",
|
|
@@ -92,8 +92,8 @@
|
|
| 92 |
"tokens_per_second": 1015177.8395898147,
|
| 93 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 94 |
"estimated_pages_for_buffer": 22,
|
| 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.",
|
|
@@ -158,24 +158,24 @@
|
|
| 158 |
"prefetch_batches": 62,
|
| 159 |
"prefetch_capacity_limit": 512,
|
| 160 |
"batch_memory_estimate_bytes": 717798,
|
| 161 |
-
"producer_batch_seconds": 0.
|
| 162 |
"producer_p95_seconds": 0.29974260100061656,
|
| 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": 32,
|
| 171 |
-
"upload_pages_per_commit":
|
| 172 |
"max_pending_pages": 4096,
|
| 173 |
-
"generation_bytes_per_second":
|
| 174 |
"upload_bytes_per_second": 4954328.8602289,
|
| 175 |
"upload_sustainable": true,
|
| 176 |
"logical_page_rows": 4096,
|
| 177 |
"logical_cortex_page_rows": 128,
|
| 178 |
-
"estimated_full_shards_per_hour": 60.
|
| 179 |
"selection_policy": "Smallest shard within 90% of measured local peak, enlarged to amortize 30 seconds of measured page production; bounded to 256 MiB."
|
| 180 |
},
|
| 181 |
"upload_measurements": [
|
|
|
|
| 22 |
"tokens_per_second": 1062967.6168812835,
|
| 23 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 24 |
"estimated_pages_for_buffer": 1,
|
| 25 |
+
"required_token_positions_per_second": 75952.4825342208,
|
| 26 |
+
"required_pages_per_second_upper_estimate": 0.006583368686259195
|
| 27 |
},
|
| 28 |
{
|
| 29 |
"source": "rewrite6",
|
|
|
|
| 36 |
"tokens_per_second": 1206672.263377472,
|
| 37 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 38 |
"estimated_pages_for_buffer": 1,
|
| 39 |
+
"required_token_positions_per_second": 9494.0603167776,
|
| 40 |
+
"required_pages_per_second_upper_estimate": 0.0037873226092139784
|
| 41 |
},
|
| 42 |
{
|
| 43 |
"source": "openmath",
|
|
|
|
| 50 |
"tokens_per_second": 410042.7581134458,
|
| 51 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 52 |
"estimated_pages_for_buffer": 1,
|
| 53 |
+
"required_token_positions_per_second": 18988.1206335552,
|
| 54 |
+
"required_pages_per_second_upper_estimate": 0.004392567529063493
|
| 55 |
},
|
| 56 |
{
|
| 57 |
"source": "ultra_qa",
|
|
|
|
| 64 |
"tokens_per_second": 2163486.5624068812,
|
| 65 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 66 |
"estimated_pages_for_buffer": 1,
|
| 67 |
+
"required_token_positions_per_second": 28482.180950332804,
|
| 68 |
+
"required_pages_per_second_upper_estimate": 0.0017344153854207246
|
| 69 |
},
|
| 70 |
{
|
| 71 |
"source": "ultra_style",
|
|
|
|
| 78 |
"tokens_per_second": 1546694.2737633225,
|
| 79 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 80 |
"estimated_pages_for_buffer": 1,
|
| 81 |
+
"required_token_positions_per_second": 28482.180950332804,
|
| 82 |
+
"required_pages_per_second_upper_estimate": 0.0021926371332797127
|
| 83 |
},
|
| 84 |
{
|
| 85 |
"source": "cortex",
|
|
|
|
| 92 |
"tokens_per_second": 1015177.8395898147,
|
| 93 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 94 |
"estimated_pages_for_buffer": 22,
|
| 95 |
+
"required_token_positions_per_second": 28482.180950332804,
|
| 96 |
+
"required_pages_per_second_upper_estimate": 0.35365336367548833
|
| 97 |
}
|
| 98 |
],
|
| 99 |
"gpu_measurement": "Selected forward/backward estimate; replaced by live successful update timings.",
|
|
|
|
| 158 |
"prefetch_batches": 62,
|
| 159 |
"prefetch_capacity_limit": 512,
|
| 160 |
"batch_memory_estimate_bytes": 717798,
|
| 161 |
+
"producer_batch_seconds": 0.08103640543748725,
|
| 162 |
"producer_p95_seconds": 0.29974260100061656,
|
| 163 |
+
"gpu_update_seconds": 0.9707121813534066,
|
| 164 |
+
"producer_batches_per_second": 12.340132741591255,
|
| 165 |
+
"gpu_batches_per_second": 1.0301714753447917,
|
| 166 |
+
"producer_headroom": 11.97871717178064,
|
| 167 |
"sustainable": true,
|
| 168 |
+
"buffer_seconds": 60.18415524391121,
|
| 169 |
"buffer_drain_seconds": null,
|
| 170 |
"shard_target_mib": 32,
|
| 171 |
+
"upload_pages_per_commit": 159,
|
| 172 |
"max_pending_pages": 4096,
|
| 173 |
+
"generation_bytes_per_second": 563978.0897682094,
|
| 174 |
"upload_bytes_per_second": 4954328.8602289,
|
| 175 |
"upload_sustainable": true,
|
| 176 |
"logical_page_rows": 4096,
|
| 177 |
"logical_cortex_page_rows": 128,
|
| 178 |
+
"estimated_full_shards_per_hour": 60.508284663127476,
|
| 179 |
"selection_policy": "Smallest shard within 90% of measured local peak, enlarged to amortize 30 seconds of measured page production; bounded to 256 MiB."
|
| 180 |
},
|
| 181 |
"upload_measurements": [
|
metrics/void-byte-v1/1790782192342215557-281f6532/train.jsonl
CHANGED
|
@@ -264,3 +264,4 @@
|
|
| 264 |
{"step": 381400, "loss": 0.5771404895931482, "lr": 0.0003, "grad_norm": 0.14902781861344497, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 55825602854, "tokens_per_second": 148512.8178592142, "data_wait_s": 9.18500154512003e-06, "gpu_peak_gb": 85.46427917480469}
|
| 265 |
{"step": 381500, "loss": 0.5936720445752144, "lr": 0.0003, "grad_norm": 0.15501056398168583, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 55840213513, "tokens_per_second": 149718.14063646214, "data_wait_s": 1.219599653268233e-05, "gpu_peak_gb": 85.46427917480469}
|
| 266 |
{"step": 381600, "loss": 0.573487963527441, "lr": 0.0003, "grad_norm": 0.1656134459225898, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 55854726840, "tokens_per_second": 147647.3880881195, "data_wait_s": 1.3763001334154978e-05, "gpu_peak_gb": 85.46427917480469}
|
|
|
|
|
|
| 264 |
{"step": 381400, "loss": 0.5771404895931482, "lr": 0.0003, "grad_norm": 0.14902781861344497, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 55825602854, "tokens_per_second": 148512.8178592142, "data_wait_s": 9.18500154512003e-06, "gpu_peak_gb": 85.46427917480469}
|
| 265 |
{"step": 381500, "loss": 0.5936720445752144, "lr": 0.0003, "grad_norm": 0.15501056398168583, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 55840213513, "tokens_per_second": 149718.14063646214, "data_wait_s": 1.219599653268233e-05, "gpu_peak_gb": 85.46427917480469}
|
| 266 |
{"step": 381600, "loss": 0.573487963527441, "lr": 0.0003, "grad_norm": 0.1656134459225898, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 55854726840, "tokens_per_second": 147647.3880881195, "data_wait_s": 1.3763001334154978e-05, "gpu_peak_gb": 85.46427917480469}
|
| 267 |
+
{"step": 381700, "loss": 0.613114608451724, "lr": 0.0003, "grad_norm": 0.15971321352573042, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 55869369087, "tokens_per_second": 149673.83336199875, "data_wait_s": 1.0146999557036906e-05, "gpu_peak_gb": 85.46427917480469}
|
runs/void-byte-v1/events.out.tfevents.1790782192.062ccfe6-664f-43fe-9e0e-62f43f0c4870-64tpq.429.0.1790782192342215557-281f6532
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d98c12469fa1d707d2aebdee0c1c1cc8c616bcb9698cf6ae1abac8bd2533ed79
|
| 3 |
+
size 569586
|