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Updated my HF Space for vibe testing smol VLMs on object detection, visual grounding, keypoint detection & counting! 👓 🆕Compare Qwen2.5 VL 3B vs Moondream 2B side-by-side with annotated images & text outputs. Try examples or test your own images! 🏃👇

15,717 views • 1 year ago •via X (Twitter)

10 Comments

Sergio Paniego's profile picture
Sergio Paniego1 year ago

📱Space: Models by @Alibaba_Qwen and @moondreamai!

merve's profile picture
merve1 year ago

@skalskip92 @vikhyatk @JustinLin610 @onuralpszr you have to see this ^

vik's profile picture
vik1 year ago

for moondream object detection prompting with just the object name will work better, that's how we train it

Sergio Paniego's profile picture
Sergio Paniego1 year ago

I was unsure whether to use the full prompt or just the object name for the examples. Let me update it to make the comparison fairer 😃

Andres Franco's profile picture
Andres Franco1 year ago

That’s impressive. Playing around with models like that must be a lot of fun.

Prithiv Sakthi 🌠's profile picture
Prithiv Sakthi 🌠1 year ago

This is really awesome 🤩

Reza Sayar's profile picture
Reza Sayar1 year ago

awesome! 👏 very useful work!! 🥳🙏

Linus | web3 mobility network nRide's profile picture
Linus | web3 mobility network nRide1 year ago

@pcuenq Vibe testing VLMs, that's really cool! I'm curious, have you explored any blockchain-based applications for object detection or visual grounding? 🤔

Onuralp S.'s profile picture
Onuralp S.1 year ago

I was experimenting with qwen and I can see it can detect each individual candies and when I ask a little bit differently it always says "colorful candies" and when I put that in to prompt I get some what better results but when I say return as "json" it just become one bbox

Johannes Gilger's profile picture
Johannes Gilger1 year ago

This is awesome, thank you so much for that. Also really helps to show the inference time. Now do all the other small-ish VLMs like Molmo, SmolVLM, InternVL, etc 😅

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