This is the Linux app named MobileCLIP whose latest release can be downloaded as ml-mobileclipsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named MobileCLIP with OnWorks for free.
Sundin ang mga tagubiling ito upang patakbuhin ang app na ito:
- 1. Na-download ang application na ito sa iyong PC.
- 2. Ipasok sa aming file manager https://www.onworks.net/myfiles.php?username=XXXXX kasama ang username na gusto mo.
- 3. I-upload ang application na ito sa naturang filemanager.
- 4. Simulan ang OnWorks Linux online o Windows online emulator o MACOS online emulator mula sa website na ito.
- 5. Mula sa OnWorks Linux OS na kasisimula mo pa lang, pumunta sa aming file manager https://www.onworks.net/myfiles.php?username=XXXX gamit ang username na gusto mo.
- 6. I-download ang application, i-install ito at patakbuhin ito.
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MobileCLIP
DESCRIPTION
MobileCLIP is a family of efficient image-text embedding models designed for real-time, on-device retrieval and zero-shot classification. The repo provides training, inference, and evaluation code for MobileCLIP models trained on DataCompDR, and for newer MobileCLIP2 models trained on DFNDR. It includes an iOS demo app and Core ML artifacts to showcase practical, offline photo search and classification on iPhone-class hardware. Project notes highlight latency/accuracy trade-offs, with MobileCLIP2 variants matching or surpassing larger baselines at notably lower parameter counts and runtime on mobile devices. A companion “mobileclip-dr” repository details large-scale, distributed data-generation pipelines used to reinforce datasets across billions of samples on thousands of GPUs. Overall, MobileCLIP emphasizes end-to-end practicality: scalable training, deployable models, and consumer-grade demos.
Mga tampok
- Efficient image-text embeddings optimized for mobile latency
- Training, inference, and evaluation pipelines for MobileCLIP and MobileCLIP2
- iOS demo app and Core ML models for offline search
- Strong accuracy at lower parameters and runtime vs larger baselines
- Dataset reinforcement tooling via the companion DR codebase
- Zero-shot retrieval and classification for on-device experiences
Wika ng Programming
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Kategorya
This is an application that can also be fetched from https://sourceforge.net/projects/mobileclip.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
