Add DoTS.ocr to documentation with official --secrets syntax

README.md

@@ -16,6 +16,7 @@ Run OCR on any dataset without needing your own GPU:
 ```bash
 # Quick test with 10 samples
 hf jobs uv run --flavor l4x1 \
+    --secrets HF_TOKEN \
     https://huggingface.co/datasets/uv-scripts/ocr/raw/main/nanonets-ocr.py \
     your-input-dataset your-output-dataset \
     --max-samples 10
@@ -71,6 +72,17 @@ Advanced reasoning-based OCR using [numind/NuMarkdown-8B-Thinking](https://huggi
 - 🔍 **Multi-column Layouts** - Handles complex document structures
 - ✨ **Thinking Traces** - Optional inclusion of reasoning process with `--include-thinking`
 
+### DoTS.ocr (`dots-ocr.py`)
+
+Compact multilingual OCR using [rednote-hilab/dots.ocr](https://huggingface.co/rednote-hilab/dots.ocr) with only 1.7B parameters:
+
+- 🌍 **100+ Languages** - Extensive multilingual support
+- 📝 **Simple OCR** - Clean text extraction (default mode)
+- 📊 **Layout Analysis** - Optional structured output with bboxes and categories
+- 📐 **Formula recognition** - LaTeX format support
+- 🎯 **Compact** - Only 1.7B parameters, efficient on smaller GPUs
+- 🔀 **Flexible prompts** - Switch between OCR, layout-all, and layout-only modes
+
 
 ## 🆕 New Features
 
@@ -118,15 +130,24 @@ No GPU? No problem! Run on HF infrastructure:
 ```bash
 # Basic OCR job
 hf jobs uv run --flavor l4x1 \
+    --secrets HF_TOKEN \
     https://huggingface.co/datasets/uv-scripts/ocr/raw/main/nanonets-ocr.py \
     your-input-dataset your-output-dataset
 
+# DoTS.ocr - Multilingual OCR with compact 1.7B model
+hf jobs uv run --flavor a100-large \
+    --secrets HF_TOKEN \
+    https://huggingface.co/datasets/uv-scripts/ocr/raw/main/dots-ocr.py \
+    davanstrien/ufo-ColPali \
+    your-username/ufo-ocr \
+    --batch-size 256 \
+    --max-samples 1000 \
+    --shuffle
 
 # Real example with UFO dataset 🛸
 hf jobs uv run \
     --flavor a10g-large \
-    --image vllm/vllm-openai:latest \
-    -s HF_TOKEN=$(python3 -c "from huggingface_hub import get_token; print(get_token())") \
+    --secrets HF_TOKEN \
     https://huggingface.co/datasets/uv-scripts/ocr/raw/main/nanonets-ocr.py \
     davanstrien/ufo-ColPali \
     your-username/ufo-ocr \
@@ -136,9 +157,8 @@ hf jobs uv run \
 
 # NuMarkdown with reasoning traces for complex documents
 hf jobs uv run \
-    --image vllm/vllm-openai:latest \
     --flavor l4x4 \
-    -s HF_TOKEN=$(python3 -c "from huggingface_hub import get_token; print(get_token())") \
+    --secrets HF_TOKEN \
     https://huggingface.co/datasets/uv-scripts/ocr/raw/main/numarkdown-ocr.py \
     your-input-dataset your-output-dataset \
     --max-samples 50 \
@@ -147,7 +167,7 @@ hf jobs uv run \
 
 # Private dataset with custom settings
 hf jobs uv run --flavor l40sx1 \
-    -s HF_TOKEN=$(python3 -c "from huggingface_hub import get_token; print(get_token())") \
+    --secrets HF_TOKEN \
     https://huggingface.co/datasets/uv-scripts/ocr/raw/main/nanonets-ocr.py \
     private-input private-output \
     --private \
@@ -205,14 +225,18 @@ Any HuggingFace dataset containing images - documents, forms, receipts, books, h
 | `--shuffle`                | False   | Shuffle dataset before processing |
 | `--seed`                   | `42`    | Random seed for shuffling     |
 
-*RolmOCR uses batch size 16
+*RolmOCR and DoTS use batch size 16
 **RolmOCR uses 16384/8192
 
-### RolmOCR Specific
+### Script-Specific Options
 
+**RolmOCR**:
 - Output column is auto-generated from model name (e.g., `rolmocr_text`)
 - Use `--output-column` to override the default name
 
-💡 **Performance tip**: Increase batch size for faster processing (e.g., `--batch-size 128` for A10G GPUs)
+**DoTS.ocr**:
+- `--prompt-mode`: Choose `ocr` (default), `layout-all`, or `layout-only`
+- `--custom-prompt`: Override with custom prompt text
+- `--output-column`: Output column name (default: `markdown`)
 
-More OCR VLM Scripts coming soon! Stay tuned for updates!
+💡 **Performance tip**: Increase batch size for faster processing (e.g., `--batch-size 256` on A100)