From: stepfun-ai <huggingface.co/stepfun-ai>Newsgroups: alt.freeweights.textSubject:

GOT-OCR2_0

Date: 2026-11-15Commit: 979938bSigned: 2DC28CC7B26A283B ✓

Image text to text model with 716M parameters. Safetensors weights, 1.44 GB in all. Published by stepfun-ai under Apache-2.0.

716M params1.44GBGOT-OCR2_0safetensorspermissive
FactsParams716MSize1.44 GBFormatssafetensorsTaskimage text to textLicenseApache-2.0From sourcepermissive
$ fw get stepfun-ai/GOT-OCR2_0
# manifest sha256 83dbb1b75407… · 1.44 GB · 15 files
$ fw verify ./GOT-OCR2_0 stepfun-ai/GOT-OCR2_0
From sourceHosted (signed)stepfun-ai/GOT-OCR2_0Last check: 2026-11-15 02:29 UTC

Get help: custom fine-tune or private deploy. We review your setup before we quote.

Runs withAIBrixBentoMLCTranslate2ExLlamaV2ExLlamaV3exofastllmFlashInferKTransformersLitServeLMCacheLMDeployLocalAImistral.rsMLC LLMMooncakeSGLangText Generation WebUItinygradTransformersTriton Inference ServervLLMXinferenceFine-tune withAccelerateAlignment HandbookAxolotlColossal-AIDeepSpeedEasyR1FlashAttentionH2O LLM StudioJAXKerasLiger KernelLitGPTLLaMA-FactoryMegatron-LMms-swiftnanotronOLMo-coreOpenRLHFOumiPEFTPyTorch Lightningsd-scriptsSimpleTunerTorchTitantorchtuneTransformer EngineTRLUnslothverlConvert withAQLMAutoRoundCore ML ToolsExecuTorchGPTQModelLLM CompressormergekitNeural CompressorOliveONNXOptimum QuantoOptimumsafetensorsTensorRT Model OptimizertorchaoEvaluate withAutoevalsDeepEvalEvaluateHELMLightEvallm-evaluation-harnessOpenCompassOpikRagassimple-evalsSWE-benchTruLensWeaveScan withAgentDojoAI Fairness 360DeepTeamDetoxifyFairlearngarakGiskardGuardrailsMCP ScannerModelScanNeMo GuardrailspicklescanpromptfooWorks withAgent Development KitAG2Google AI Edge GalleryAiderany-llmAnythingLLMBAMLbrowser-useCAMELHugging Face Chat UIChatboxCherry StudioClineCodex CLICogneeCrewAIDeerFlowdocTRDSPyEasyOCREnchantedGemini CLIGitHub MCP ServergooseGPT ResearcherGradioGraphitiGuidanceHollamaInstructorKilo CodeLangflowLangGraphLiteLLMLlamaIndexLLMLocalAGILoLLMs WebUIMCP Python SDKMem0MetaGPTNextChatOllama JavaScriptOllama PythonolmOCROpenAI Agents SDKopencodeOpenHandsotermOutlinesPage AssistPlaywright MCPPortkey AI GatewayPrivateGPTQwen CodeRWKV RunnerSemantic KernelsmolagentsStrands AgentsSuryaVaneXGrammar

Overview

Size
1.44 GB
Weights
1.43 GB (safetensors)
Parameters
716M
Formats
safetensors
Task
image text to text
License
Apache-2.0 (permissive)
Files
15, each with a sha256
Publisher
stepfun-ai
Added
2026-11-15
Section
alt.freeweights.text
Lineage

Original release from the publisher.

Where these bytes come from
Publisher at the pinned commit→You

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Sources
BadgeHostLast checkResult
From sourcehuggingface.co2026-11-15 02:29 UTCpassed

Model card

From the publisher at commit 979938b. Shown as plain text with links; images open at the publisher.

General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model#

🔋Online Demo | 🌟GitHub | 📜Paper

Haoran Wei*, Chenglong Liu*, Jinyue Chen, Jia Wang, Lingyu Kong, Yanming Xu, Zheng Ge, Liang Zhao, Jianjian Sun, Yuang Peng, Chunrui Han, Xiangyu Zhang

Image: image/jpeg

Usage#

Inference using Huggingface transformers on NVIDIA GPUs. Requirements tested on python 3.10:

torch==2.0.1
torchvision==0.15.2
transformers==4.37.2
tiktoken==0.6.0
verovio==4.3.1
accelerate==0.28.0
from transformers import AutoModel, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained('ucaslcl/GOT-OCR2_0', trust_remote_code=True)
model = AutoModel.from_pretrained('ucaslcl/GOT-OCR2_0', trust_remote_code=True, low_cpu_mem_usage=True, device_map='cuda', use_safetensors=True, pad_token_id=tokenizer.eos_token_id)
model = model.eval().cuda()


# input your test image
image_file = 'xxx.jpg'

# plain texts OCR
res = model.chat(tokenizer, image_file, ocr_type='ocr')

# format texts OCR:
# res = model.chat(tokenizer, image_file, ocr_type='format')

# fine-grained OCR:
# res = model.chat(tokenizer, image_file, ocr_type='ocr', ocr_box='')
# res = model.chat(tokenizer, image_file, ocr_type='format', ocr_box='')
# res = model.chat(tokenizer, image_file, ocr_type='ocr', ocr_color='')
# res = model.chat(tokenizer, image_file, ocr_type='format', ocr_color='')

# multi-crop OCR:
# res = model.chat_crop(tokenizer, image_file, ocr_type='ocr')
# res = model.chat_crop(tokenizer, image_file, ocr_type='format')

# render the formatted OCR results:
# res = model.chat(tokenizer, image_file, ocr_type='format', render=True, save_render_file = './demo.html')

print(res)

More details about 'ocr_type', 'ocr_box', 'ocr_color', and 'render' can be found at our GitHub. Our training codes are available at our GitHub.

More Multimodal Projects#

👏 Welcome to explore more multimodal projects of our team:

Vary | Fox | OneChart

Citation#

If you find our work helpful, please consider citing our papers 📝 and liking this project ❤️!

@article{wei2024general,
  title={General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model},
  author={Wei, Haoran and Liu, Chenglong and Chen, Jinyue and Wang, Jia and Kong, Lingyu and Xu, Yanming and Ge, Zheng and Zhao, Liang and Sun, Jianjian and Peng, Yuang and others},
  journal={arXiv preprint arXiv:2409.01704},
  year={2024}
}
@article{liu2024focus,
  title={Focus Anywhere for Fine-grained Multi-page Document Understanding},
  author={Liu, Chenglong and Wei, Haoran and Chen, Jinyue and Kong, Lingyu and Ge, Zheng and Zhu, Zining and Zhao, Liang and Sun, Jianjian and Han, Chunrui and Zhang, Xiangyu},
  journal={arXiv preprint arXiv:2405.14295},
  year={2024}
}
@article{wei2023vary,
  title={Vary: Scaling up the Vision Vocabulary for Large Vision-Language Models},
  author={Wei, Haoran and Kong, Lingyu and Chen, Jinyue and Zhao, Liang and Ge, Zheng and Yang, Jinrong and Sun, Jianjian and Han, Chunrui and Zhang, Xiangyu},
  journal={arXiv preprint arXiv:2312.06109},
  year={2023}
}

Files

15 files · 1.44 GBWeights 1.43 GB (safetensors). Sizes and sha256 from the signed manifest.
Hide all 15 files with their sha256
FileSizesha256
.gitattributes1.52 KB11ad7efa24975ee4b0c3c3a38ed18737f0658a5f75a0a96787b576a78a023361
README.md3.96 KB1c8697ddeb841080c25a06b2eadd9dbdf714cdef886fb457a2568b57b2079134
assets/got_logo.png511 KBcf9a90a822ef9d521ba0f9702b50cbd7a8a37e5661f0792a94a009deb9511de7
assets/got_support.jpg198 KBc4d78f00966111b9a8ba838f8ab0ad6a1e2e9fdf91ccf7790915808aca2fada0
assets/train_sample.jpg155 KB3839e3b1a775ba710d01097dc84d7e8bf2609c3f8ba52a6e810660044d856362
config.json986 B59db7f1fc9346e596221a1af3d836b11148d6ac5e6344f64f34820df672ac629
generation_config.json117 B64e4f9d67c678c6dd6b1ac2f1b0d2562ae12cec463493ce2951daf1dba4e494f
got_vision_b.py16.1 KB8931c2e1145afa6e99aa707fa73ab24afabe3ad69fe5341a5b7160e2688cf750
model.safetensors1.43 GB77d6144039548b14253176b6eb264896bc39eba532f8894700f210a7fd2a5956
modeling_GOT.py33.8 KB68375b6bf7683cca41bb987953f0e31fde802652ad01e1accc4b53127b841609
qwen.tiktoken2.56 MBb2b1b8dfb5cc5f024bafc373121c6aba3f66f9a5a0269e243470a1de16a33186
render_tools.py1.99 KB11393028ac7095431cfaa9c8ee14b9c6e8ca1d618158dfe729b89e83e889fb99
special_tokens_map.json149 B337f1a03344485ec7ea2acd6f7021567feab077fd81f96b72423fcd3f8f5fc09
tokenization_qwen.py9.47 KBeec08335cdcdcb538120e204f19b41bbd9e5ab989e14b1b1cf8f506ac584c601
tokenizer_config.json300 B0a0f9a1847cf1bc7d09ebcc1ae8d6a43f71cc6ff1821096102c5db8d387018d4
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
979938bf89 pinned now2026-11-15 02:29 UTC15 files · 1.44 GB

Use it

$ fw get stepfun-ai/GOT-OCR2_0
# manifest sha256 83dbb1b75407… · 1.44 GB · 15 files
$ fw verify ./GOT-OCR2_0 stepfun-ai/GOT-OCR2_0
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/stepfun-ai/GOT-OCR2_0.json --dir ./GOT-OCR2_0 $ python3 fw.py verify ./GOT-OCR2_0 ./stepfun-ai__GOT-OCR2_0.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download stepfun-ai/GOT-OCR2_0 --revision 979938bf89ccdc949c0131ddd3841e24578a4742 --local-dir ./GOT-OCR2_0
transformersLoad the weights in Python.
import os os.environ["HF_ENDPOINT"] = "https://freeweights.allternit.com" from transformers import AutoModelForImageTextToText, AutoProcessor processor = AutoProcessor.from_pretrained("stepfun-ai/GOT-OCR2_0", revision="979938bf89ccdc949c0131ddd3841e24578a4742") model = AutoModelForImageTextToText.from_pretrained("stepfun-ai/GOT-OCR2_0", revision="979938bf89ccdc949c0131ddd3841e24578a4742", device_map="auto")
vLLMServe an OpenAI-compatible API.
$ HF_ENDPOINT=https://freeweights.allternit.com vllm serve stepfun-ai/GOT-OCR2_0 --revision 979938bf89ccdc949c0131ddd3841e24578a4742

License

Name
Apache License 2.0
Id
Apache-2.0
Class
Permissive
Redistribution
yes
Listing
Hosted (signed)
Decided
License as declared by the publisher. No person read it. 2026-11-15
Text in
README.md
Text sha256
1c8697ddeb841080c25a06b2eadd9dbdf714cdef886fb457a2568b57b2079134
Terms gate
No extra terms beyond the license.

Read the license text

Licenses are checked against the license table. A custom license passes only after a person reads it.

Provenance

From: stepfun-ai <huggingface.co/stepfun-ai>Newsgroups: alt.freeweights.textSubject: GOT-OCR2_0Date: 2026-11-15Commit: 979938bSigned: 2DC28CC7B26A283B ✓
Upstream
stepfun-ai/GOT-OCR2_0
Pinned commit
979938bf89ccdc949c0131ddd3841e24578a4742
Manifest
GOT-OCR2_0.json · .minisig
Manifest sha256
83dbb1b75407ffa5fafdfd415d009f65f4badcd803f52ed42bafe77a979c39d8
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 02:29 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/stepfun-ai/GOT-OCR2_0.json $ curl -O https://freeweights.allternit.com/manifests/stepfun-ai/GOT-OCR2_0.json.minisig $ minisign -Vm GOT-OCR2_0.json -P RWQ7KGqyx4zCLXtUFOqvfv8L3g+8fpKJ1FsuxPyOYMF+4KufbUxKq1Oq $ shasum -a 256 <file> # compare with the Files tab

A manifest whose signature fails must be rejected. A file whose size or sha256 does not match must be discarded. Verify a download

Model tree

1 model in the catalog name this one as their parent.

Quantizations
1
Quantizations 1
Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download stepfun-ai/GOT-OCR2_0
Open in Freeweights Studio

Pull, verify and run it in the Allternit app on Desktop, web or phone.

Signed manifest
minisign, key 2DC28CC7B26A283B. GOT-OCR2_0.json. Provenance. Takedown history: none.

Variants

1 quantized or adapter build of GOT-OCR2_0. Each has its own license check and page.

From: laion <huggingface.co/laion>Subject: a2-rl-e2egit_large-50-32B
From: laion <huggingface.co/laion>Subject: a3-rl-DCAgent_exp_rpt_e2egit-large-15-8B
From: laion <huggingface.co/laion>Subject: a3-rl-DCAgent_exp_rpt_e2egit-v2-10-8B
From: laion <huggingface.co/laion>Subject: a3-rl-DCAgent_exp_rpt_pymethods2test-large-80-8B
From: laion <huggingface.co/laion>Subject: a3-rl-DCAgent_exp_rpt_unitsyn-python-large-10-8B
From: laion <huggingface.co/laion>Subject: a3-rl-DCAgent_mix_h2_language_proportional-65-8B