Fix volume mount syntax in falcon-ocr-bucket.py examples
davanstrien+1: Claude Opus 4.6 (1M context)HF Staff
0b77b50
The hf jobs CLI expects 'hf://buckets/' (plural) not 'bucket/'.
Verified working end-to-end: 376 PDF pages OCR'd in 11.9 min on L4.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Add Falcon OCR bucket script for directory/volume I/O
davanstrien+1: Claude Opus 4.6 (1M context)HF Staff
d0a2ced
Companion to falcon-ocr.py (dataset mode). Reads images/PDFs from a
directory, writes markdown files preserving structure. Designed for
HF Buckets mounted as volumes via -v flag.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
davanstrien+1: Claude Opus 4.6 (1M context)HF Staff
173e9b8
New OCR script using tiiuae/Falcon-OCR with the optimized falcon-perception
inference engine (CUDA graphs + batched paged inference). Achieves 0.31 img/s
on L4, 0.53 img/s on L40S. Supports plain OCR and layout-aware extraction.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
davanstrien+1: Claude Opus 4.6 (1M context)HF Staff
dafc1a9
- dots.mocr is the official final name for what was dots.ocr-1.5
- Model now on HF directly: rednote-hilab/dots.mocr (no ModelScope mirror needed)
- Added SVG prompt mode (--prompt-mode svg) with auto temperature/top_p
- SVG-optimized variant: rednote-hilab/dots.mocr-svg
- Updated README with new model entry and detailed docs
- Tested: OCR mode 3/3 on L4, SVG mode 3/3 on L4
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Fix dots-ocr-1.5.py for v1.5 model + document bbox coords
davanstrien+1: Claude Opus 4.6 (1M context)HF Staff
37431e4
- Add chat_template_content_format="string" to llm.chat() (required for
dots.ocr-1.5 which uses a string-only tokenizer chat template)
- Document bbox coordinate system (Qwen2VL smart_resize) in script and CLAUDE.md
- Fix README table link to point to davanstrien/dots.ocr-1.5 mirror
- Add full dots.ocr-1.5 section to CLAUDE.md with test results and usage notes
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- New firered-ocr.py using llm.chat() pattern from dots-ocr.py
- Model: FireRedTeam/FireRed-OCR (Apache 2.0)
- Tested: 10/10 on ufo-ColPali, L4 GPU, ~4.7 min
- Stable vLLM (>=0.15.1), no nightly needed
- README: added to model table and per-model docs
Pin dots-ocr-1.5.py + ocr-vllm-judge.py to stable vLLM (>=0.15.1)
- Pin vLLM >=0.15.1 (was >=0.9.1) to match other production scripts
- Add limit_mm_per_prompt={"image": 1} to LLM init for stable batch processing
- On batch failure, retry images individually so only broken images get [OCR ERROR]
Tested: 20/20 samples clean on A100 (davanstrien/ufo-ColPali, seed 42)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
CommitScheduler uploads parquet batches in background (results never
lost on crash/timeout). --resume picks up from last completed batch.
CleanupScheduler deletes local shards after upload to prevent disk fill.
Validated on full 2724-page Encyclopaedia Britannica run (~$5, 0 errors).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Restructure README: cleaner intro, TOC table, common options
- Punchier intro with model count (13 models, 0.9B-8B)
- Quick start example switched to GLM-OCR
- Added collapsible TOC table with all scripts sorted by model size
- Moved common options section up with --help tip
- Added GLM-OCR usage example (OCR, table, formula modes)
- Collapsed detailed per-model docs into expandable section
- Stripped most emoji from headings
- Fixed stale PaddleOCR SOTA claim (GLM-OCR now scores higher)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Pin nanonets-ocr2.py + paddleocr-vl.py to stable vLLM (>=0.15.1)
Both use architectures in stable vLLM. Also pins datasets>=4.0.0
and drops nightly index from paddleocr-vl.py.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Pin nanonets-ocr.py to stable vLLM (>=0.15.1) + datasets>=4.0.0
RolmOCR (Qwen2.5-VL fine-tune) is in stable vLLM. Note: 8B model
needs a100 or larger GPU (OOMs on L4 with default max_model_len=16384).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Rewrite evaluation prompt to prioritize faithfulness over formatting,
heavily penalizing added commentary/interpretation
- Add --save-results flag to push judge results (comparisons, leaderboard,
metadata) to HF Hub dataset repo
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Switch hunyuan-ocr.py to stable vLLM (>=0.15.1), drop nightly index
HunyuanOCR architecture is in stable vLLM. Also pins datasets>=4.0.0
and removes disable_mm_preprocessor_cache (nightly-only arg).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Switch deepseek-ocr-vllm.py to stable vLLM (>=0.15.1), drop nightly index
LightOnOCR-2 architecture is in stable vLLM since 0.15.1.
Also bumps datasets>=4.0.0 and drops pyarrow<18 pin.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Pin numarkdown-ocr.py to stable vLLM (>=0.15.1) + datasets>=4.0.0
Qwen2.5-VL architecture is in stable vLLM, no nightly needed.
Pinning datasets>=4.0.0 fixes pyarrow compatibility.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Fix config_name=None breaking push_to_hub + use cu129 nightly index
- Replace config_name=config with conditional spread to avoid passing
None, which generates invalid YAML (config_name: null) that fails
Hub validation. Applied to all 10 scripts with --config flag.
- Switch vLLM nightly URL from /nightly to /nightly/cu129 in 6 scripts
to get x86_64 wheels (bare /nightly only has ARM wheels currently).
- Includes accumulated improvements: --verbose flag, --config/--create-pr
support, upload retry with XET fallback, inference_info fixes.
- Adds dots-ocr-1.5.py and hunyuan-ocr.py (new scripts).
Verified via HF Jobs smoke tests (7/9 config-flag scripts completed).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
DeepSeek-OCR-2 model card only documents two prompts.
Remove image/figure/describe modes carried over from v1.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Switch back to nightly vLLM, add addict + matplotlib deps
DeepSeek-OCR-2 is not in stable vLLM 0.15.1 yet (only nightly).
The nightly x86_64 builds are back (dev142). Also add addict and
matplotlib which the model's custom code requires.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Use stable vLLM (>=0.15.1) instead of nightly for DeepSeek-OCR-2
DeepSeek-OCR-2 support is in stable vLLM 0.15.1 (released Feb 5, 2026).
The nightly index currently only has ARM wheels, breaking x86_64 Jobs.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add DeepSeek-OCR-2 vLLM script (rewrite from fixed v1 pattern)
Rewrites the broken draft (base64/llm.chat/resolution modes) to use the
proven v1 pattern: llm.generate() with PIL images + NGramPerReqLogitsProcessor.
Key v2 change: limit_mm_per_prompt={"image": 1} for the new architecture.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Rewrote inference core to match the official vLLM DeepSeek-OCR recipe:
- llm.generate() with PIL images instead of llm.chat() with base64
- Added NGramPerReqLogitsProcessor to prevent repetition loops
- Added enable_prefix_caching=False, mm_processor_cache_gb=0
- Added skip_special_tokens=False and ngram/window sampling params
- Removed resolution modes (only apply to transformers API, not vLLM)
- Removed deprecated HF_XET_HIGH_PERFORMANCE env var
- Bumped script_version to 2.0.0
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Update nanonets-ocr.py HF Jobs syntax and add smoke test notes
- Replace deprecated `hfjobs run` with current `hf jobs uv run` syntax
- Add OCR smoke test dataset design notes to CLAUDE.md
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replace fragile git dep with stable transformers>=5.1.0 for GLM-OCR
GLM-OCR support landed in transformers v5.1.0. The previous unpinned git
dependency could break at any commit. Also updated docstring to note vLLM
nightly was re-verified on 2026-02-12.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
GLM-OCR SDK sets max_tokens=16384 but our max_model_len is 8192.
vLLM silently caps generation, making the high default misleading.
Align default to 8192 and document the SDK discrepancy.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Remove `[hf_transfer]` extra from PEP 723 dependencies (5 scripts)
- Replace `HF_HUB_ENABLE_HF_TRANSFER=1` with `HF_XET_HIGH_PERFORMANCE=1` (4 scripts)
- Hub now uses Xet storage backend; hf_transfer is deprecated
Ref: https://huggingface.co/docs/huggingface_hub/package_reference/environment_variables#hfxethighperformance
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Standardizing metadata tags across uv-scripts organization
for better discoverability of HF Jobs-compatible scripts.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
