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": 21,
|
| 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": 61,
|
| 159 |
"prefetch_capacity_limit": 512,
|
| 160 |
"batch_memory_estimate_bytes": 688946,
|
| 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": 4695517.6851320835,
|
| 175 |
"upload_sustainable": true,
|
| 176 |
"logical_page_rows": 4096,
|
| 177 |
"logical_cortex_page_rows": 128,
|
| 178 |
-
"estimated_full_shards_per_hour":
|
| 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": 74105.52193015984,
|
| 26 |
+
"required_pages_per_second_upper_estimate": 0.006423278822178045
|
| 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": 9263.19024126998,
|
| 40 |
+
"required_pages_per_second_upper_estimate": 0.003695225084278754
|
| 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": 18526.38048253996,
|
| 54 |
+
"required_pages_per_second_upper_estimate": 0.004285752071475225
|
| 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": 27789.570723809942,
|
| 68 |
+
"required_pages_per_second_upper_estimate": 0.0016922390564705024
|
| 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": 27789.570723809942,
|
| 82 |
+
"required_pages_per_second_upper_estimate": 0.002139318080774165
|
| 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": 21,
|
| 95 |
+
"required_token_positions_per_second": 27789.570723809942,
|
| 96 |
+
"required_pages_per_second_upper_estimate": 0.34505346267938886
|
| 97 |
}
|
| 98 |
],
|
| 99 |
"gpu_measurement": "Selected forward/backward estimate; replaced by live successful update timings.",
|
|
|
|
| 158 |
"prefetch_batches": 61,
|
| 159 |
"prefetch_capacity_limit": 512,
|
| 160 |
"batch_memory_estimate_bytes": 688946,
|
| 161 |
+
"producer_batch_seconds": 0.07913221451562791,
|
| 162 |
+
"producer_p95_seconds": 0.14340419199993448,
|
| 163 |
+
"gpu_update_seconds": 0.9949056167431675,
|
| 164 |
+
"producer_batches_per_second": 12.63707841516945,
|
| 165 |
+
"gpu_batches_per_second": 1.0051204688878017,
|
| 166 |
+
"producer_headroom": 12.572700294475931,
|
| 167 |
"sustainable": true,
|
| 168 |
+
"buffer_seconds": 60.689242621333214,
|
| 169 |
"buffer_drain_seconds": null,
|
| 170 |
"shard_target_mib": 16,
|
| 171 |
+
"upload_pages_per_commit": 71,
|
| 172 |
"max_pending_pages": 4096,
|
| 173 |
+
"generation_bytes_per_second": 466573.9417329422,
|
| 174 |
"upload_bytes_per_second": 4695517.6851320835,
|
| 175 |
"upload_sustainable": true,
|
| 176 |
"logical_page_rows": 4096,
|
| 177 |
"logical_cortex_page_rows": 128,
|
| 178 |
+
"estimated_full_shards_per_hour": 100.11590661040496,
|
| 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-v1/1790476562033999719-ba4f58e1/train.jsonl
CHANGED
|
@@ -9,3 +9,4 @@
|
|
| 9 |
{"step": 82800, "loss": 0.5665384028106928, "lr": 0.0003, "grad_norm": 0.13098018386505245, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 12117034475, "tokens_per_second": 145526.04640431632, "data_wait_s": 1.0684000017135986e-05, "gpu_peak_gb": 85.46427917480469}
|
| 10 |
{"step": 82900, "loss": 0.5804585367441177, "lr": 0.0003, "grad_norm": 0.13427587039895614, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 12131681070, "tokens_per_second": 149314.93150573867, "data_wait_s": 1.162500007012568e-05, "gpu_peak_gb": 85.46427917480469}
|
| 11 |
{"step": 83000, "loss": 0.6183635629713535, "lr": 0.0003, "grad_norm": 0.13188186813879005, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 12146491385, "tokens_per_second": 150376.761259858, "data_wait_s": 1.3017000128456857e-05, "gpu_peak_gb": 85.46427917480469}
|
|
|
|
|
|
| 9 |
{"step": 82800, "loss": 0.5665384028106928, "lr": 0.0003, "grad_norm": 0.13098018386505245, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 12117034475, "tokens_per_second": 145526.04640431632, "data_wait_s": 1.0684000017135986e-05, "gpu_peak_gb": 85.46427917480469}
|
| 10 |
{"step": 82900, "loss": 0.5804585367441177, "lr": 0.0003, "grad_norm": 0.13427587039895614, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 12131681070, "tokens_per_second": 149314.93150573867, "data_wait_s": 1.162500007012568e-05, "gpu_peak_gb": 85.46427917480469}
|
| 11 |
{"step": 83000, "loss": 0.6183635629713535, "lr": 0.0003, "grad_norm": 0.13188186813879005, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 12146491385, "tokens_per_second": 150376.761259858, "data_wait_s": 1.3017000128456857e-05, "gpu_peak_gb": 85.46427917480469}
|
| 12 |
+
{"step": 83100, "loss": 0.6229391451925039, "lr": 0.0003, "grad_norm": 0.13720698418826618, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 86, "input_bytes_and_specials": 12160969657, "tokens_per_second": 146814.05009065697, "data_wait_s": 1.158499981102068e-05, "gpu_peak_gb": 85.46427917480469}
|
runs/void-byte-v1/events.out.tfevents.1790476562.0b09bbb2-f535-42d2-bd00-cbae7fb94f51-r2qrq.417.0.1790476562033999719-ba4f58e1
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 sha256:92982570bcd02057ad2ef0ec6db8b30d2144e7ac60651b30c76efb4cefc835a3
|
| 3 |
+
size 25581
|