Document the Gemma 3 4B IT recaptions

README.md

@@ -184,6 +184,21 @@ Same code, prompt, sampling (`n=2`, temperature 0.8, top-p 0.9, at most 160 new
 
 A manual check of 24 captions (12 images) found the main subject and its count, colors, setting, medium and legible text correct in all of them; 5 had one wrong secondary detail (an action, a clothing item, a person count, the spelling of a name, a left/right reference). No invented objects were found. Compared with the Qwen2.5-VL-3B captions, the two Gemma captions of an image are closer to each other (39% of the content words of `recap_2` are not in `recap_1`, against 57%): they mostly state the same facts in different words, with one or two different secondary details. Captions from different models (Gemma, Qwen2.5-VL-3B, the original Qwen2.5-VL-7B caption) differ more. Openings are formulaic: about 28% of captions start with "A single".
 
+
+## Gemma 3 4B IT recaptions
+
+`gemma-3-4b-it-recaptions/<shard>.parquet` holds one new caption for each of the first 500,000 images (subset `index` 0–499,999). The captions were written by [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it) with vLLM 0.33.0, greedy decoding, and the same prompt as the Qwen3-VL-8B recaptions. See `gemma-3-4b-it-recaptions/README.md`. Join on `key`.
+
+```python
+from datasets import load_dataset
+
+gemma3 = load_dataset(
+    "parquet",
+    data_files="hf://datasets/IntelligenceLab/BLIP3o-Recap/gemma-3-4b-it-recaptions/*.parquet",
+    split="train",
+)
+```
+
 ## License
 
 Apache-2.0, same as the source dataset.