Text Generation
Transformers
Safetensors
mistral3
image-text-to-text
decision-model
typed-decisions
jev
jevbench
calibration
decode-free
multilingual
vision-language
conversational
Instructions to use StandardThinking/StandardOne-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StandardThinking/StandardOne-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="StandardThinking/StandardOne-3B") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("StandardThinking/StandardOne-3B") model = AutoModelForMultimodalLM.from_pretrained("StandardThinking/StandardOne-3B", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use StandardThinking/StandardOne-3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "StandardThinking/StandardOne-3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "StandardThinking/StandardOne-3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/StandardThinking/StandardOne-3B
- SGLang
How to use StandardThinking/StandardOne-3B 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 "StandardThinking/StandardOne-3B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "StandardThinking/StandardOne-3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "StandardThinking/StandardOne-3B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "StandardThinking/StandardOne-3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use StandardThinking/StandardOne-3B with Docker Model Runner:
docker model run hf.co/StandardThinking/StandardOne-3B
File size: 11,335 Bytes
09d4173 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 | <?xml version="1.0" encoding="utf-8" standalone="no"?>
<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN"
"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
<svg xmlns:xlink="http://www.w3.org/1999/xlink" width="827.044531pt" height="284.483104pt" viewBox="0 0 827.044531 284.483104" xmlns="http://www.w3.org/2000/svg" version="1.1">
<metadata>
<rdf:RDF xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://creativecommons.org/ns#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#">
<cc:Work>
<dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/>
<dc:date>2026-09-24T18:00:38.044364</dc:date>
<dc:format>image/svg+xml</dc:format>
<dc:creator>
<cc:Agent>
<dc:title>Matplotlib v3.11.2, https://matplotlib.org/</dc:title>
</cc:Agent>
</dc:creator>
</cc:Work>
</rdf:RDF>
</metadata>
<defs>
<style type="text/css">*{stroke-linejoin: round; stroke-linecap: butt}</style>
</defs>
<g id="figure_1">
<g id="patch_1">
<path d="M 0 284.483104
L 827.044531 284.483104
L 827.044531 0
L 0 0
z
" style="fill: #fcfcfb"/>
</g>
<g id="axes_1">
<g id="patch_2">
<path d="M 136.130937 225.142281
L 638.330938 225.142281
L 638.330938 25.558281
L 136.130937 25.558281
z
" style="fill: #fcfcfb"/>
</g>
<g id="matplotlib.axis_1">
<g id="xtick_1">
<g id="line2d_1">
<path d="M 136.130937 225.142281
L 136.130937 25.558281
" clip-path="url(#p08aabe4cac)" style="fill: none; stroke: #e6e5e1; stroke-linecap: square"/>
</g>
<g id="line2d_2"/>
<g id="text_1">
<text style="font-size: 11px; font-family: 'DejaVu Sans'; text-anchor: middle" x="136.130937" y="236.999703" transform="rotate(-0 136.130937 236.999703)">0</text>
</g>
</g>
<g id="xtick_2">
<g id="line2d_3">
<path d="M 236.570937 225.142281
L 236.570937 25.558281
" clip-path="url(#p08aabe4cac)" style="fill: none; stroke: #e6e5e1; stroke-linecap: square"/>
</g>
<g id="line2d_4"/>
<g id="text_2">
<text style="font-size: 11px; font-family: 'DejaVu Sans'; text-anchor: middle" x="236.570937" y="236.999703" transform="rotate(-0 236.570937 236.999703)">20</text>
</g>
</g>
<g id="xtick_3">
<g id="line2d_5">
<path d="M 337.010937 225.142281
L 337.010937 25.558281
" clip-path="url(#p08aabe4cac)" style="fill: none; stroke: #e6e5e1; stroke-linecap: square"/>
</g>
<g id="line2d_6"/>
<g id="text_3">
<text style="font-size: 11px; font-family: 'DejaVu Sans'; text-anchor: middle" x="337.010937" y="236.999703" transform="rotate(-0 337.010937 236.999703)">40</text>
</g>
</g>
<g id="xtick_4">
<g id="line2d_7">
<path d="M 437.450938 225.142281
L 437.450938 25.558281
" clip-path="url(#p08aabe4cac)" style="fill: none; stroke: #e6e5e1; stroke-linecap: square"/>
</g>
<g id="line2d_8"/>
<g id="text_4">
<text style="font-size: 11px; font-family: 'DejaVu Sans'; text-anchor: middle" x="437.450938" y="236.999703" transform="rotate(-0 437.450938 236.999703)">60</text>
</g>
</g>
<g id="xtick_5">
<g id="line2d_9">
<path d="M 537.890937 225.142281
L 537.890937 25.558281
" clip-path="url(#p08aabe4cac)" style="fill: none; stroke: #e6e5e1; stroke-linecap: square"/>
</g>
<g id="line2d_10"/>
<g id="text_5">
<text style="font-size: 11px; font-family: 'DejaVu Sans'; text-anchor: middle" x="537.890937" y="236.999703" transform="rotate(-0 537.890937 236.999703)">80</text>
</g>
</g>
<g id="xtick_6">
<g id="line2d_11">
<path d="M 638.330938 225.142281
L 638.330938 25.558281
" clip-path="url(#p08aabe4cac)" style="fill: none; stroke: #e6e5e1; stroke-linecap: square"/>
</g>
<g id="line2d_12"/>
<g id="text_6">
<text style="font-size: 11px; font-family: 'DejaVu Sans'; text-anchor: middle" x="638.330938" y="236.999703" transform="rotate(-0 638.330938 236.999703)">100</text>
</g>
</g>
<g id="text_7">
<text style="font-size: 11px; font-family: 'DejaVu Sans'; text-anchor: middle" x="387.230937" y="252.000563" transform="rotate(-0 387.230937 252.000563)">latency per decision, serial (ms) — bar = p50, dot = p95</text>
</g>
</g>
<g id="matplotlib.axis_2">
<g id="ytick_1">
<g id="line2d_13"/>
<g id="text_8">
<text style="font-size: 11px; font-family: 'DejaVu Sans'; text-anchor: end; fill: #0b0b0b" x="132.630937" y="61.489422" transform="rotate(-0 132.630937 61.489422)">Standard One 3B</text>
</g>
</g>
<g id="ytick_2">
<g id="line2d_14"/>
<g id="text_9">
<text style="font-size: 11px; font-family: 'DejaVu Sans'; text-anchor: end; fill: #0b0b0b" x="132.630937" y="106.849422" transform="rotate(-0 132.630937 106.849422)">Standard One 8B</text>
</g>
</g>
<g id="ytick_3">
<g id="line2d_15"/>
<g id="text_10">
<text style="font-size: 11px; font-family: 'DejaVu Sans'; text-anchor: end; fill: #0b0b0b" x="132.630937" y="152.209422" transform="rotate(-0 132.630937 152.209422)">Qwen3-8B (untuned)</text>
</g>
</g>
<g id="ytick_4">
<g id="line2d_16"/>
<g id="text_11">
<text style="font-size: 11px; font-family: 'DejaVu Sans'; text-anchor: end; fill: #0b0b0b" x="132.630937" y="197.569422" transform="rotate(-0 132.630937 197.569422)">Qwen3.5-4B (untuned)</text>
</g>
</g>
</g>
<g id="patch_3">
<path d="M 136.633137 69.557481
L 249.125937 69.557481
Q 249.628137 69.557481 249.628137 65.021481
L 249.628137 49.599081
Q 249.628137 45.063081 249.125937 45.063081
L 136.633137 45.063081
Q 136.130937 45.063081 136.130937 49.599081
L 136.130937 65.021481
Q 136.130937 69.557481 136.633137 69.557481
z
" clip-path="url(#p08aabe4cac)" style="fill: #2a78d6"/>
</g>
<g id="patch_4">
<path d="M 136.633137 114.917481
L 265.196338 114.917481
Q 265.698537 114.917481 265.698537 110.381481
L 265.698537 94.959081
Q 265.698537 90.423081 265.196338 90.423081
L 136.633137 90.423081
Q 136.130937 90.423081 136.130937 94.959081
L 136.130937 110.381481
Q 136.130937 114.917481 136.633137 114.917481
z
" clip-path="url(#p08aabe4cac)" style="fill: #2a78d6"/>
</g>
<g id="patch_5">
<path d="M 136.633137 160.277481
L 278.755738 160.277481
Q 279.257938 160.277481 279.257938 155.741481
L 279.257938 140.319081
Q 279.257938 135.783081 278.755738 135.783081
L 136.633137 135.783081
Q 136.130937 135.783081 136.130937 140.319081
L 136.130937 155.741481
Q 136.130937 160.277481 136.633137 160.277481
z
" clip-path="url(#p08aabe4cac)" style="fill: #c3c2b7"/>
</g>
<g id="patch_6">
<path d="M 136.633137 205.637481
L 380.702337 205.637481
Q 381.204538 205.637481 381.204538 201.101481
L 381.204538 185.679081
Q 381.204538 181.143081 380.702337 181.143081
L 136.633137 181.143081
Q 136.130937 181.143081 136.130937 185.679081
L 136.130937 201.101481
Q 136.130937 205.637481 136.633137 205.637481
z
" clip-path="url(#p08aabe4cac)" style="fill: #c3c2b7"/>
</g>
<g id="line2d_17">
<path d="M 249.628137 57.310281
L 302.861337 57.310281
" clip-path="url(#p08aabe4cac)" style="fill: none; stroke: #52514e; stroke-width: 1.5; stroke-linecap: square"/>
</g>
<g id="line2d_18">
<path d="M 265.698537 102.670281
L 346.552737 102.670281
" clip-path="url(#p08aabe4cac)" style="fill: none; stroke: #52514e; stroke-width: 1.5; stroke-linecap: square"/>
</g>
<g id="line2d_19">
<path d="M 279.257938 148.030281
L 423.389338 148.030281
" clip-path="url(#p08aabe4cac)" style="fill: none; stroke: #52514e; stroke-width: 1.5; stroke-linecap: square"/>
</g>
<g id="line2d_20">
<path d="M 381.204538 193.390281
L 501.230338 193.390281
" clip-path="url(#p08aabe4cac)" style="fill: none; stroke: #52514e; stroke-width: 1.5; stroke-linecap: square"/>
</g>
<g id="patch_7">
<path d="M 136.130937 225.142281
L 638.330938 225.142281
" style="fill: none; stroke: #e6e5e1; stroke-width: 0.8; stroke-linejoin: miter; stroke-linecap: square"/>
</g>
<g id="PathCollection_1">
<defs>
<path id="mfb5be21640" d="M 0 2.645751
C 0.701661 2.645751 1.374679 2.366978 1.870829 1.870829
C 2.366978 1.374679 2.645751 0.701661 2.645751 0
C 2.645751 -0.701661 2.366978 -1.374679 1.870829 -1.870829
C 1.374679 -2.366978 0.701661 -2.645751 0 -2.645751
C -0.701661 -2.645751 -1.374679 -2.366978 -1.870829 -1.870829
C -2.366978 -1.374679 -2.645751 -0.701661 -2.645751 0
C -2.645751 0.701661 -2.366978 1.374679 -1.870829 1.870829
C -1.374679 2.366978 -0.701661 2.645751 0 2.645751
z
" style="stroke: #52514e"/>
</defs>
<g clip-path="url(#p08aabe4cac)">
<use xlink:href="#mfb5be21640" x="302.861337" y="57.310281" style="fill: #52514e; stroke: #52514e"/>
</g>
</g>
<g id="text_12">
<text style="font-weight: 700; font-size: 9.5px; font-family: 'DejaVu Sans'; text-anchor: start; fill: #0b0b0b" x="310.394338" y="59.778055" transform="rotate(-0 310.394338 59.778055)">p50 23 ms · p95 33 ms</text>
</g>
<g id="PathCollection_2">
<g clip-path="url(#p08aabe4cac)">
<use xlink:href="#mfb5be21640" x="346.552737" y="102.670281" style="fill: #52514e; stroke: #52514e"/>
</g>
</g>
<g id="text_13">
<text style="font-weight: 700; font-size: 9.5px; font-family: 'DejaVu Sans'; text-anchor: start; fill: #0b0b0b" x="354.085737" y="105.138055" transform="rotate(-0 354.085737 105.138055)">p50 26 ms · p95 42 ms</text>
</g>
<g id="PathCollection_3">
<g clip-path="url(#p08aabe4cac)">
<use xlink:href="#mfb5be21640" x="423.389338" y="148.030281" style="fill: #52514e; stroke: #52514e"/>
</g>
</g>
<g id="text_14">
<text style="font-size: 9.5px; font-family: 'DejaVu Sans'; text-anchor: start; fill: #0b0b0b" x="430.922338" y="150.498055" transform="rotate(-0 430.922338 150.498055)">p50 28 ms · p95 57 ms</text>
</g>
<g id="PathCollection_4">
<g clip-path="url(#p08aabe4cac)">
<use xlink:href="#mfb5be21640" x="501.230338" y="193.390281" style="fill: #52514e; stroke: #52514e"/>
</g>
</g>
<g id="text_15">
<text style="font-size: 9.5px; font-family: 'DejaVu Sans'; text-anchor: start; fill: #0b0b0b" x="508.763338" y="195.858055" transform="rotate(-0 508.763338 195.858055)">p50 49 ms · p95 73 ms</text>
</g>
<g id="text_16">
<text style="font-weight: 700; font-size: 11px; font-family: 'DejaVu Sans'; text-anchor: start; fill: #0b0b0b" x="136.130937" y="15.558281" transform="rotate(-0 136.130937 15.558281)">Same stack, same 242-decision profile: one H200, SGLang 0.5.20, jev-adapter, ~280 input tokens per decision</text>
</g>
</g>
<g id="text_17">
<text style="font-size: 8.5px; font-family: 'DejaVu Sans'; fill: #52514e" transform="translate(61.610937 264.187957)">Qwen rows are the untuned instruct checkpoints (Qwen3-8B, Qwen3.5-4B) served through the same adapter for a speed reference only; no accuracy comparison is implied.</text>
<text style="font-size: 8.5px; font-family: 'DejaVu Sans'; fill: #52514e" transform="translate(61.610937 274.390281)">Leaderboard Speed applies ×2 + 0.15 s to self-hosted latency.</text>
</g>
</g>
<defs>
<clipPath id="p08aabe4cac">
<rect x="136.130937" y="25.558281" width="502.2" height="199.584"/>
</clipPath>
</defs>
</svg>
|