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 530000; complete resumable checkpoint
Browse files- complete.json +6 -6
- coverage.json +45 -45
- latest.json +1 -1
- model.safetensors +1 -1
- performance.json +3 -3
- shard_scheduler.json +100 -328
- trainer.pt +2 -2
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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"selected": {
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shard_scheduler.json
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| 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,
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| 81 |
-
"required_token_positions_per_second":
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| 82 |
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"required_pages_per_second_upper_estimate": 0.
|
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},
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{
|
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"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": 23,
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| 95 |
-
"required_token_positions_per_second":
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| 96 |
-
"required_pages_per_second_upper_estimate": 0.
|
| 97 |
}
|
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],
|
| 99 |
"gpu_measurement": "Selected forward/backward estimate; replaced by live successful update timings.",
|
|
@@ -158,410 +158,182 @@
|
|
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"prefetch_batches": 63,
|
| 159 |
"prefetch_capacity_limit": 512,
|
| 160 |
"batch_memory_estimate_bytes": 704566,
|
| 161 |
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| 162 |
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| 163 |
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| 164 |
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-
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|
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-
"producer_headroom":
|
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"sustainable": true,
|
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-
"buffer_seconds": 60.
|
| 169 |
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| 170 |
"shard_target_mib": 16,
|
| 171 |
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"upload_pages_per_commit":
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"max_pending_pages": 4096,
|
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"generation_bytes_per_second":
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"upload_bytes_per_second":
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"upload_sustainable": true,
|
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|
| 177 |
"logical_cortex_page_rows": 128,
|
| 178 |
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"estimated_full_shards_per_hour": 82.
|
| 179 |
"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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},
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"upload_measurements": [
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"cache_key": {
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|
@@ -606,7 +378,7 @@
|
|
| 606 |
},
|
| 607 |
"cache_reused": true,
|
| 608 |
"resume_probe_seconds": [
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| 609 |
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1.
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| 610 |
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0.
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]
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| 612 |
}
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|
|
|
| 22 |
"tokens_per_second": 598315.063954628,
|
| 23 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
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| 24 |
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| 25 |
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"required_pages_per_second_upper_estimate": 0.005328144519284888
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| 27 |
},
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{
|
| 29 |
"source": "rewrite6",
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|
|
|
| 36 |
"tokens_per_second": 8533.957213384612,
|
| 37 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
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| 38 |
"estimated_pages_for_buffer": 1,
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| 39 |
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"required_token_positions_per_second": 9626.99808033432,
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| 40 |
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| 41 |
},
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| 42 |
{
|
| 43 |
"source": "openmath",
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|
|
|
| 50 |
"tokens_per_second": 380144.35761751566,
|
| 51 |
"note": "Bounded fresh sample; full-page latency is an extrapolation.",
|
| 52 |
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| 53 |
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"required_token_positions_per_second": 19253.99616066864,
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| 54 |
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| 55 |
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| 56 |
{
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| 57 |
"source": "ultra_qa",
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|
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|
trainer.pt
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 sha256:4273939d74c5226bc57df9a209306193dff7da001a42417dfdf439575063da35
|
| 3 |
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size 721771007
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