TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #15600 · Apr 4
#python#apple_silicon#florence2#idefics#llava#llm#local_ai#mlx#molmo#paligemma#pixtral#vision_framework#vision_language_model#vision_transformer MLX-VLM lets you run, chat with, and fine-tune Vision Language Models (VLMs) plus audio/video models on your Mac using MLX—install easily with `pip install -U mlx-vlm`. Use CLI for quick text/image/audio generation (e.g., `mlx_vlm.generate --model ... --image photo.jpg`), Gradio UI for chats, Python scripts, or a FastAPI server with OpenAI-compatible endpoints supporting multi-images/videos. Features like TurboQuant cut KV cache memory by 76%, and LoRA/QLoRA fine-tuning works on consumer hardware. You benefit by experimenting with powerful multimodal AI locally—fast, memory-efficient, no cloud costs, perfect for Mac users tweaking models affordably. https://github.com/Blaizzy/mlx-vlm
Search: #dl
@repo_science · Post #4131 · 05/18/2024, 09:06 PM
#DL 📱 Zeus New Pytorch Ecosystem Tool Zeus is an open source toolkit for measuring and optimizing power consumption of deep learning workloads. 🖥Github ----- Main channel: @repo_science Coupons: @freecoupons_reposcience -----
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@amneumarkt · Post #706 · 11/21/2025, 07:53 AM
#dl Introducing more symmetries in attention https://github.com/NVIDIA/torch-harmonics https://neurips.cc/virtual/2025/loc/san-diego/poster/117783
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@amneumarkt · Post #691 · 10/05/2025, 07:41 AM
#dl Park, Chanwook, Sourav Saha, Jiachen Guo, Hantao Zhang, Xiaoyu Xie, Miguel A. Bessa, Dong Qian, et al. 2025. “Unifying Machine Learning and Interpolation Theory via Interpolating Neural Networks.” Nature Communications 16 (1): 1–12. https://www.nature.com/articles/s41467-025-63790-8
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@amneumarkt · Post #683 · 06/28/2025, 07:04 AM
#dl A few cool ideas in this model. Introducing Gemma 3n: The developer guide - Google Developers Blog https://developers.googleblog.com/en/introducing-gemma-3n-developer-guide/
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@amneumarkt · Post #681 · 06/14/2025, 08:43 AM
#dl So tensorflow and jax are deprecated in the transformers package. https://github.com/huggingface/transformers/pull/38758
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@amneumarkt · Post #662 · 02/21/2025, 07:42 AM
#dl Sure, nobody uses it anyways.
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@amneumarkt · Post #625 · 10/03/2024, 09:31 PM
#dl PyTorch Native Architecture Optimization: torchao | PyTorch https://pytorch.org/blog/pytorch-native-architecture-optimization/
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@amneumarkt · Post #624 · 10/03/2024, 06:07 PM
#dl https://soumith.ch/blog/2024-10-02-training-10k-scale.md.html
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@amneumarkt · Post #602 · 07/20/2024, 05:48 AM
#dl There is this new lib called scale. One could compile CUDA code to use it on AMD GPU. https://docs.scale-lang.com/manual/how-to-use/ I don't know who is more pissed off, NVidia or AMD.
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@amneumarkt · Post #556 · 03/16/2024, 09:09 AM
#dl This repo is really nice. yuanchenyang/smalldiffusion: Simple and readable code for training and sampling from diffusion models https://github.com/yuanchenyang/smalldiffusion
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@amneumarkt · Post #506 · 11/13/2023, 08:30 AM
#dl Google & USC benchmarked a prompt based forecasting method, and the results are amazing. Cao D, Jia F, Arik SO, Pfister T, Zheng Y, Ye W, et al. TEMPO: Prompt-based Generative Pre-trained Transformer for time series forecasting. arXiv [cs.LG]. 2023. Available: http://arxiv.org/abs/2310.04948
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@amneumarkt · Post #484 · 06/12/2023, 06:13 AM
#dl https://twitter.com/armin_kekic/status/1667181047480479751?s=20
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