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": 598315.063954628,
|
| 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": 8533.957213384612,
|
| 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": 380144.35761751566,
|
| 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": 43742.16556775435,
|
| 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": 22018.86276523721,
|
| 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": 910315.184299418,
|
| 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": 720750,
|
| 161 |
-
"producer_batch_seconds": 0.
|
| 162 |
"producer_p95_seconds": 0.20482549900043523,
|
| 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": 83,
|
| 172 |
"max_pending_pages": 4096,
|
| 173 |
-
"generation_bytes_per_second":
|
| 174 |
"upload_bytes_per_second": 4764394.786287227,
|
| 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": 598315.063954628,
|
| 23 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 24 |
"estimated_pages_for_buffer": 1,
|
| 25 |
+
"required_token_positions_per_second": 76036.33865079588,
|
| 26 |
+
"required_pages_per_second_upper_estimate": 0.005260370336474848
|
| 27 |
},
|
| 28 |
{
|
| 29 |
"source": "rewrite6",
|
|
|
|
| 36 |
"tokens_per_second": 8533.957213384612,
|
| 37 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 38 |
"estimated_pages_for_buffer": 1,
|
| 39 |
+
"required_token_positions_per_second": 9504.542331349485,
|
| 40 |
+
"required_pages_per_second_upper_estimate": 0.003979353396722531
|
| 41 |
},
|
| 42 |
{
|
| 43 |
"source": "openmath",
|
|
|
|
| 50 |
"tokens_per_second": 380144.35761751566,
|
| 51 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 52 |
"estimated_pages_for_buffer": 1,
|
| 53 |
+
"required_token_positions_per_second": 19009.08466269897,
|
| 54 |
+
"required_pages_per_second_upper_estimate": 0.003959091031966455
|
| 55 |
},
|
| 56 |
{
|
| 57 |
"source": "ultra_qa",
|
|
|
|
| 64 |
"tokens_per_second": 43742.16556775435,
|
| 65 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 66 |
"estimated_pages_for_buffer": 1,
|
| 67 |
+
"required_token_positions_per_second": 28513.626994048453,
|
| 68 |
+
"required_pages_per_second_upper_estimate": 0.0017093484005057044
|
| 69 |
},
|
| 70 |
{
|
| 71 |
"source": "ultra_style",
|
|
|
|
| 78 |
"tokens_per_second": 22018.86276523721,
|
| 79 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 80 |
"estimated_pages_for_buffer": 1,
|
| 81 |
+
"required_token_positions_per_second": 28513.626994048453,
|
| 82 |
+
"required_pages_per_second_upper_estimate": 0.0022168090805967234
|
| 83 |
},
|
| 84 |
{
|
| 85 |
"source": "cortex",
|
|
|
|
| 92 |
"tokens_per_second": 910315.184299418,
|
| 93 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 94 |
"estimated_pages_for_buffer": 22,
|
| 95 |
+
"required_token_positions_per_second": 28513.626994048453,
|
| 96 |
+
"required_pages_per_second_upper_estimate": 0.36574219153228477
|
| 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": 720750,
|
| 161 |
+
"producer_batch_seconds": 0.3159707569609367,
|
| 162 |
"producer_p95_seconds": 0.20482549900043523,
|
| 163 |
+
"gpu_update_seconds": 0.9696416385670917,
|
| 164 |
+
"producer_batches_per_second": 3.1648498412263812,
|
| 165 |
+
"gpu_batches_per_second": 1.031308846717609,
|
| 166 |
+
"producer_headroom": 3.0687701858655485,
|
| 167 |
"sustainable": true,
|
| 168 |
+
"buffer_seconds": 60.11778159115969,
|
| 169 |
"buffer_drain_seconds": null,
|
| 170 |
"shard_target_mib": 16,
|
| 171 |
"upload_pages_per_commit": 83,
|
| 172 |
"max_pending_pages": 4096,
|
| 173 |
+
"generation_bytes_per_second": 475510.09989054175,
|
| 174 |
"upload_bytes_per_second": 4764394.786287227,
|
| 175 |
"upload_sustainable": true,
|
| 176 |
"logical_page_rows": 4096,
|
| 177 |
"logical_cortex_page_rows": 128,
|
| 178 |
+
"estimated_full_shards_per_hour": 102.03339812791052,
|
| 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-v1/1791209746770022608-f3fe5fb7/train.jsonl
CHANGED
|
@@ -109,3 +109,4 @@
|
|
| 109 |
{"step": 730900, "loss": 0.5254196524620056, "lr": 5e-05, "grad_norm": 0.20506942528752026, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 90, "input_bytes_and_specials": 106983059087, "tokens_per_second": 152802.7041302198, "data_wait_s": 9.747000149218366e-06, "gpu_peak_gb": 89.37899398803711}
|
| 110 |
{"step": 731000, "loss": 0.5641935467720032, "lr": 5e-05, "grad_norm": 0.2287241484936114, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 90, "input_bytes_and_specials": 106997690229, "tokens_per_second": 151364.96428365033, "data_wait_s": 1.3975999536341988e-05, "gpu_peak_gb": 89.37899398803711}
|
| 111 |
{"step": 731100, "loss": 0.7164812088012695, "lr": 5e-05, "grad_norm": 0.32625489069749375, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 90, "input_bytes_and_specials": 107012288288, "tokens_per_second": 148174.05047318505, "data_wait_s": 1.487400004407391e-05, "gpu_peak_gb": 89.37899398803711}
|
|
|
|
|
|
| 109 |
{"step": 730900, "loss": 0.5254196524620056, "lr": 5e-05, "grad_norm": 0.20506942528752026, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 90, "input_bytes_and_specials": 106983059087, "tokens_per_second": 152802.7041302198, "data_wait_s": 9.747000149218366e-06, "gpu_peak_gb": 89.37899398803711}
|
| 110 |
{"step": 731000, "loss": 0.5641935467720032, "lr": 5e-05, "grad_norm": 0.2287241484936114, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 90, "input_bytes_and_specials": 106997690229, "tokens_per_second": 151364.96428365033, "data_wait_s": 1.3975999536341988e-05, "gpu_peak_gb": 89.37899398803711}
|
| 111 |
{"step": 731100, "loss": 0.7164812088012695, "lr": 5e-05, "grad_norm": 0.32625489069749375, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 90, "input_bytes_and_specials": 107012288288, "tokens_per_second": 148174.05047318505, "data_wait_s": 1.487400004407391e-05, "gpu_peak_gb": 89.37899398803711}
|
| 112 |
+
{"step": 731200, "loss": 0.5573129653930664, "lr": 5e-05, "grad_norm": 0.22699834790070478, "recovery_retries": 0, "loss_scale": 1.0, "microbatch": 90, "input_bytes_and_specials": 107026740621, "tokens_per_second": 149328.75677081733, "data_wait_s": 1.4477000149781816e-05, "gpu_peak_gb": 89.37899398803711}
|
runs/void-byte-v1/events.out.tfevents.1791209746.ebd20fd8-0561-42d8-bf2b-56d08e7106ef-6qqk2.329.0.1791209746770022608-f3fe5fb7
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:d3ac4ca648bdf0e2172d5991661829387c0899e9e0d3fd2babe80d3aa41e24ae
|
| 3 |
+
size 238947
|