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/61ba93d7df85017c130f96aa6408d72bc25b0578/coverage.json
- Command line
-
hf download hf://dotlabs/void.1@61ba93d7df85017c130f96aa6408d72bc25b0578/coverage.json
-
curl -L -o coverage.json https://huggingface.co/dotlabs/void.1/resolve/61ba93d7df85017c130f96aa6408d72bc25b0578/coverage.json
2.29 kB
| { | |
| "step": 390000, | |
| "stats": { | |
| "climbmix/blocks": 14040000, | |
| "climbmix/targets": 23469768992, | |
| "climbmix/input_tokens": 23471255758, | |
| "ultra_qa/blocks": 5265000, | |
| "ultra_qa/targets": 8589103233, | |
| "ultra_qa/input_tokens": 8589119791, | |
| "cortex/blocks": 5265000, | |
| "cortex/targets": 200266960, | |
| "cortex/input_tokens": 8369485865, | |
| "ultra_style/blocks": 5265000, | |
| "ultra_style/targets": 8328115889, | |
| "ultra_style/input_tokens": 8328552449, | |
| "openmath/blocks": 3510000, | |
| "openmath/targets": 5423887511, | |
| "openmath/input_tokens": 5425694857, | |
| "rewrite6/blocks": 1755000, | |
| "rewrite6/targets": 2877105386, | |
| "rewrite6/input_tokens": 2880259808 | |
| }, | |
| "sources": { | |
| "climbmix": { | |
| "page": 1922, | |
| "row": 3973, | |
| "start": { | |
| "file": 93, | |
| "reader": { | |
| "format": "parquet-row-v1", | |
| "row_group": 3, | |
| "row": 1024 | |
| } | |
| }, | |
| "epoch": 0, | |
| "offset": 6144, | |
| "documents": 7876485 | |
| }, | |
| "rewrite6": { | |
| "page": 44, | |
| "row": 214, | |
| "start": { | |
| "file": 0, | |
| "reader": { | |
| "format": "jsonl-row-v1", | |
| "row": 180224 | |
| } | |
| }, | |
| "epoch": 21, | |
| "offset": 0, | |
| "documents": 4493922 | |
| }, | |
| "openmath": { | |
| "page": 1201, | |
| "row": 3048, | |
| "start": { | |
| "file": 11, | |
| "reader": { | |
| "format": "parquet-row-v1", | |
| "row_group": 116, | |
| "row": 146 | |
| } | |
| }, | |
| "epoch": 0, | |
| "offset": 0, | |
| "documents": 4922344 | |
| }, | |
| "ultra_qa": { | |
| "page": 519, | |
| "row": 2369, | |
| "start": { | |
| "file": 4, | |
| "reader": { | |
| "format": "parquet-row-v1", | |
| "row_group": 0, | |
| "row": 47323 | |
| } | |
| }, | |
| "epoch": 0, | |
| "offset": 2048, | |
| "documents": 2128193 | |
| }, | |
| "ultra_style": { | |
| "page": 793, | |
| "row": 45, | |
| "start": { | |
| "file": 4, | |
| "reader": { | |
| "format": "parquet-row-v1", | |
| "row_group": 5, | |
| "row": 82015 | |
| } | |
| }, | |
| "epoch": 0, | |
| "offset": 0, | |
| "documents": 3248173 | |
| }, | |
| "cortex": { | |
| "page": 102116, | |
| "row": 47, | |
| "start": null, | |
| "epoch": 0, | |
| "offset": 0, | |
| "documents": 13070895 | |
| } | |
| } | |
| } |