rednote-hilab

dots.ocr

Name: dots.ocr
Author: rednote-hilab

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3B parameters · Base · dots.ocr family

mit hash verified source matched revision pinned

Which version should I download?

Default pick: safetensors · BF16 — BF16 source weights (rednote-hilab/dots.ocr, MIT-based license) — reference multilingual document-OCR VLM. Community GGUFs are generic auto-quant on a custom arch; safetensors is the reliable format (Transformers/vLLM). Full repo bundled.

Set your rig to confirm it fits and to see if a higher-quality quant runs fully on your hardware.

Set your rig

Quantizations

Why these quants? Which quant should I pick?

Format	Level	Size	Verdict	Est. speed	Quality note	Swarm	Download
safetensors	BF16	5.66 GB	Set your rig	—	BF16 source weights (rednote-hilab/dots.ocr, MIT-based license) — reference multilingual document-OCR VLM. Community GGUFs are generic auto-quant on a custom arch; safetensors is the reliable format (Transformers/vLLM). Full repo bundled.	2S / 0L webseed OK	Magnet .torrent

safetensors · BF16

5.66 GB

Set your rig

Est. speed: —
Swarm: 2S / 0L webseed OK

BF16 source weights (rednote-hilab/dots.ocr, MIT-based license) — reference multilingual document-OCR VLM. Community GGUFs are generic auto-quant on a custom arch; safetensors is the reliable format (Transformers/vLLM). Full repo bundled.

Magnet .torrent

Run it

Runtime completeness (BF16 torrent): llama.cpp – Ollama – vision sidecar –

– llama.cpp — no GGUF artifact for this torrent
– Ollama — not an Ollama-native artifact
– vision sidecar — not a vision model

Quant

Context / KV 8,192 tokens · FP16 set above the quant table

Generic commands (no rig set). GPU-offload values assume the model fits on your GPU — set your rig for values tuned to your hardware.

Start the server

llama-server -m rednote-hilab-dots-ocr-BF16.gguf -c 8192 -ngl 999

Use llama-cli in place of llama-server for a one-shot prompt.

Save as Modelfile next to the GGUF (Modelfile)

FROM ./rednote-hilab-dots-ocr-BF16.gguf
PARAMETER num_ctx 8192
PARAMETER num_gpu 999

Create

ollama create rednote-hilab-dots-ocr -f Modelfile

Run

ollama run rednote-hilab-dots-ocr

Serve an OpenAI-compatible endpoint

vllm serve rednote-hilab/dots.ocr --max-model-len 8192

Serves on http://localhost:8000/v1 by default.

Load rednote-hilab-dots-ocr-BF16.gguf, set the context length to 8192 tokens. Set GPU offload to Max (all layers).

Not an MLX-format quant.

MLX runs MLX-format weights only (Apple Silicon). This quant is not an MLX build.

Filename shown is a placeholder. The exact GGUF name appears once the download is available.

Technical details

No template or sampling metadata recorded.

Evidence & provenance

Source

Provenance: https://huggingface.co/rednote-hilab/dots.ocr
Revision pin: c0111ce6bc07803dbc267932ffef0ae3a51dc951
Manifest: Present

License

Name: mit
Commercial use: yes
Access: Open

File hashes (SHA-256)

dots-ocr/.gitattributes 11ad7efa24975ee4b0c3c3a38ed18737f0658a5f75a0a96787b576a78a023361
dots-ocr/LICENSE b34e9d9a83c0fadcbe7e3e53d850ccf9b2f99dfa2bd0cd6772fe3dfbb07c4af6
dots-ocr/NOTICE df6e0c47ba4b8eaf130e578a097a027ca06c8b13efd03c5539a3f6c68b0211cc
dots-ocr/README.md e59f00e56945936a65c74cf53333a9051715ba45e91da0b7d86cd05f5964c2eb
dots-ocr/chat_template.json 315c86fc560a11463ab2360aea5c7001c56533cb7229ee5cbcaaecca6d210698
dots-ocr/config.json 41d5c9aad72c730bb97062cab7a59cdb1d427eeec0b7a6e2f95e1ee72ad3b498
dots-ocr/configuration_dots.py e86a4fd70c6f21178c57112c44d5cc64b8ee02e3e8ad8cafe00045c0844b931b
dots-ocr/generation_config.json daaf4cfc2d4bd75bc68d07a8e51dcfb464f99e59a8d69772b25f1c793c7b3cdf
dots-ocr/merges.txt 599bab54075088774b1733fde865d5bd747cbcc7a547c5bc12610e874e26f5e3
dots-ocr/model-00001-of-00002.safetensors ea1d532184f3adf5cbcfcc00b2cf5b2abfa6fe182768a3ae63d441a9b5fc99ac
dots-ocr/model-00002-of-00002.safetensors 26ab1ec6c8b4e4116befbd59af42159f1dbcb0ad0c045a15e890bb2f6e8b0dae
dots-ocr/model.safetensors.index.json 90b4c82045a7d1343348d59c584d124a9cc0e23f3ca8b7d81250e93030924842
dots-ocr/modeling_dots_ocr.py 274b5bfa35f624f15001da70414e733b89f5cb44b5453d80023bff26a68d0135
dots-ocr/modeling_dots_ocr_vllm.py fc70aa417e8c0f5589366fbdc789193c97f4c4d0a094f867b222092188b68b19
dots-ocr/modeling_dots_vision.py 9fb57cce892e6f065ff86b6f02fbd72110fe6d9f749c2ae8c82897068bbed877
dots-ocr/preprocessor_config.json fec8b3187ab0ae340f6d0b1f6f892a53c63b73b328836c83dd7bff1d5bc4c79a
dots-ocr/special_tokens_map.json 92b060f39417514eed2f7652f454a3d5afb0e4a57b9f4b51dd4d1dfd8fdb9736
dots-ocr/tokenizer.json 386545eb05f08c51352cde2fcc2c867f1592bb330f305efd1c6a57a93b1244cd
dots-ocr/tokenizer_config.json 4f09a26dd6b20c82e9678d96b7363a58a778a948a21261d3315a949d47ed4cf4
dots-ocr/vocab.json ca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910

Performance reports

Real-world throughput reported by the community (and scraped sources).

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Reviews & presets

Reviews (0)

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Sampler presets

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Community runtime reports

Unofficial, community-submitted "it loads for me" reports. These are not the official verified-working badge — an admin reviews reports before anything is marked officially verified.

No community reports yet.

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