ngxson
/

tinygemma3_cifar

@@ -5,197 +5,62 @@ tags:
 - sft
 ---
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 - sft
 ---
+# tinygemma3 with vision
+This is trained on [CIFAR-10](https://huggingface.co/datasets/uoft-cs/cifar10) dataset.
+How to use:
+```py
+from transformers import AutoModelForImageTextToText, AutoProcessor
+model_id = "ngxson/tinygemma3_v0"
+model = AutoModelForImageTextToText.from_pretrained(model_id).to("cuda")
+processor = AutoProcessor.from_pretrained(model_id)
+#####################
+from datasets import load_dataset, Dataset
+ds_full = load_dataset("uoft-cs/cifar10")
+def ex_to_msg(ex):
+    txt = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "What is this:"},
+                {"type": "image"}
+            ]
+        }
+    ]
+    img = ex["img"]
+    return {
+        "messages": txt,
+        "images": [img],
+    }
+#####################
+test_idx = 0
+test_msg = ex_to_msg(ds_full["train"][test_idx])
+test_txt = processor.apply_chat_template(test_msg["messages"], tokenize=False, add_generation_prompt=True)
+test_input = processor(text=test_txt, images=test_msg["images"], return_tensors="pt").to(model.device)
+#####################
+generated_ids = model.generate(**test_input, do_sample=False, max_new_tokens=1)
+generated_texts = processor.batch_decode(
+    generated_ids,
+    skip_special_tokens=True,
+)
+print(generated_texts)
+# expected answer for test_idx = 0 is "airplane"
+```