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
Download coverage.json from dotlabs/void.1: direct link, hf CLI and curl.
- Browser
- Download file 2.29 kB
-
https://huggingface.co/dotlabs/void.1/resolve/a3f42dbd079e18ffbfd1d8a2bb33dbd81f8ddc14/coverage.json
- Command line
-
hf download hf://dotlabs/void.1@a3f42dbd079e18ffbfd1d8a2bb33dbd81f8ddc14/coverage.json
-
curl -L -o coverage.json https://huggingface.co/dotlabs/void.1/resolve/a3f42dbd079e18ffbfd1d8a2bb33dbd81f8ddc14/coverage.json
2.29 kB
| { | |
| "step": 270000, | |
| "stats": { | |
| "climbmix/blocks": 9720000, | |
| "climbmix/targets": 16248306295, | |
| "climbmix/input_tokens": 16249336141, | |
| "ultra_qa/blocks": 3645000, | |
| "ultra_qa/targets": 5946191498, | |
| "ultra_qa/input_tokens": 5946202929, | |
| "cortex/blocks": 3645000, | |
| "cortex/targets": 138670584, | |
| "cortex/input_tokens": 5793992704, | |
| "ultra_style/blocks": 3645000, | |
| "ultra_style/targets": 5765190778, | |
| "ultra_style/input_tokens": 5765493512, | |
| "openmath/blocks": 2430000, | |
| "openmath/targets": 3754982954, | |
| "openmath/input_tokens": 3756234898, | |
| "rewrite6/blocks": 1215000, | |
| "rewrite6/targets": 1991834205, | |
| "rewrite6/input_tokens": 1994017932 | |
| }, | |
| "sources": { | |
| "climbmix": { | |
| "page": 1331, | |
| "row": 746, | |
| "start": { | |
| "file": 64, | |
| "reader": { | |
| "format": "parquet-row-v1", | |
| "row_group": 35, | |
| "row": 1024 | |
| } | |
| }, | |
| "epoch": 0, | |
| "offset": 12288, | |
| "documents": 5452522 | |
| }, | |
| "rewrite6": { | |
| "page": 7, | |
| "row": 1260, | |
| "start": { | |
| "file": 0, | |
| "reader": { | |
| "format": "jsonl-row-v1", | |
| "row": 28672 | |
| } | |
| }, | |
| "epoch": 15, | |
| "offset": 0, | |
| "documents": 3110992 | |
| }, | |
| "openmath": { | |
| "page": 832, | |
| "row": 915, | |
| "start": { | |
| "file": 7, | |
| "reader": { | |
| "format": "parquet-row-v1", | |
| "row_group": 351, | |
| "row": 322 | |
| } | |
| }, | |
| "epoch": 0, | |
| "offset": 0, | |
| "documents": 3408787 | |
| }, | |
| "ultra_qa": { | |
| "page": 359, | |
| "row": 2968, | |
| "start": { | |
| "file": 2, | |
| "reader": { | |
| "format": "parquet-row-v1", | |
| "row_group": 6, | |
| "row": 43713 | |
| } | |
| }, | |
| "epoch": 0, | |
| "offset": 2048, | |
| "documents": 1473432 | |
| }, | |
| "ultra_style": { | |
| "page": 549, | |
| "row": 1375, | |
| "start": { | |
| "file": 3, | |
| "reader": { | |
| "format": "parquet-row-v1", | |
| "row_group": 2, | |
| "row": 23029 | |
| } | |
| }, | |
| "epoch": 0, | |
| "offset": 2048, | |
| "documents": 2250079 | |
| }, | |
| "cortex": { | |
| "page": 70690, | |
| "row": 82, | |
| "start": null, | |
| "epoch": 0, | |
| "offset": 0, | |
| "documents": 9048402 | |
| } | |
| } | |
| } |