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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 次观看 • 1 年前 •via X (Twitter)

10 条评论

Sergio Paniego 的头像
Sergio Paniego1 年前

📱Space: Models by @Alibaba_Qwen and @moondreamai!

merve 的头像
merve1 年前

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

vik 的头像
vik1 年前

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

Sergio Paniego 的头像
Sergio Paniego1 年前

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 的头像
Andres Franco1 年前

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

Prithiv Sakthi 🌠 的头像
Prithiv Sakthi 🌠1 年前

This is really awesome 🤩

Reza Sayar 的头像
Reza Sayar1 年前

awesome! 👏 very useful work!! 🥳🙏

Linus | web3 mobility network nRide 的头像
Linus | web3 mobility network nRide1 年前

@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. 的头像
Onuralp S.1 年前

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 的头像
Johannes Gilger1 年前

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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