Add hf-jobs tag to README frontmatter

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>

README.md

@@ -1,6 +1,6 @@
 ---
 viewer: false
-tags: [uv-script, vllm, gpu, inference]
+tags: [uv-script, vllm, gpu, inference, hf-jobs]
 ---
 
 # vLLM Inference Scripts
@@ -11,6 +11,67 @@ These scripts use [UV's inline script metadata](https://docs.astral.sh/uv/guides
 
 ## 📋 Available Scripts
 
+### vlm-classify.py
+
+Vision Language Model (VLM) image classification with structured output constraints.
+
+**Features:**
+
+- 🖼️ Process images through state-of-the-art VLMs (Qwen2-VL)
+- 🎯 Structured classification using vLLM's `GuidedDecodingParams`
+- 📐 Automatic image resizing to optimize token usage
+- 💾 Memory-efficient lazy batch processing
+- 🏷️ Simple CLI interface for defining classes
+- 🤗 Direct integration with Hugging Face datasets
+
+**Usage:**
+
+```bash
+# Basic classification
+uv run vlm-classify.py \
+    username/input-dataset \
+    username/output-dataset \
+    --classes "document,photo,diagram,other"
+
+# With custom prompt and image resizing
+uv run vlm-classify.py \
+    username/input-dataset \
+    username/output-dataset \
+    --classes "index-card,manuscript,title-page,other" \
+    --prompt "What type of historical document is this?" \
+    --max-size 768
+
+# Quick test with sample limit
+uv run vlm-classify.py \
+    davanstrien/sloane-index-cards \
+    username/test-output \
+    --classes "index,content,other" \
+    --max-samples 10
+```
+
+**HF Jobs execution:**
+
+```bash
+hf jobs uv run \
+    --flavor a10g \
+    --image vllm/vllm-openai \
+    -s HF_TOKEN \
+    https://huggingface.co/datasets/uv-scripts/vllm/raw/main/vlm-classify.py \
+    username/input-dataset \
+    username/output-dataset \
+    --classes "title-page,content,index,other" \
+    --max-size 768
+```
+
+**Key Parameters:**
+
+- `--classes`: Comma-separated list of classification categories (required)
+- `--prompt`: Custom classification prompt (optional, auto-generated if not provided)
+- `--max-size`: Maximum image dimension in pixels for resizing (reduces token count)
+- `--model`: VLM model to use (default: Qwen/Qwen2-VL-7B-Instruct)
+- `--batch-size`: Number of images to process at once (default: 8)
+- `--max-samples`: Limit number of samples for testing
+
 ### classify-dataset.py
 
 Batch text classification using BERT-style encoder models (e.g., BERT, RoBERTa, DeBERTa, ModernBERT) with vLLM's optimized inference engine.
@@ -101,7 +162,7 @@ hf jobs uv run \
     --flavor l4x4 \
     --image vllm/vllm-openai \
     -e UV_PRERELEASE=if-necessary \
-    -s HF_TOKEN=hf_*** \
+    -s HF_TOKEN \
     https://huggingface.co/datasets/uv-scripts/vllm/raw/main/generate-responses.py \
     davanstrien/cards_with_prompts \
     davanstrien/test-generated-responses \