@Machine_learn
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LLaMA-Omni: Seamless Speech Interaction with Large Language Models
Paper: https://arxiv.org/pdf/2409.06666v1.pdf
Code: https://github.com/ictnlp/llama-omni
✅ @Machine_learn
Paper: https://arxiv.org/pdf/2409.06666v1.pdf
Code: https://github.com/ictnlp/llama-omni
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MiniCPM-V
MiniCPM-V 2.6: A GPT-4V Level MLLM for Single Image, Multi Image and Video on Your Phone
Creator: OpenBMB
Stars ⭐️: 11.4k
Forked By: 798
GitHub Repo:
https://github.com/OpenBMB/MiniCPM-V
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Join✅ https://t.iss.one/deep_learning_proj
✅ @Machine_learn
MiniCPM-V 2.6: A GPT-4V Level MLLM for Single Image, Multi Image and Video on Your Phone
Creator: OpenBMB
Stars ⭐️: 11.4k
Forked By: 798
GitHub Repo:
https://github.com/OpenBMB/MiniCPM-V
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Join
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GitHub
GitHub - OpenBMB/MiniCPM-o: MiniCPM-o 2.6: A GPT-4o Level MLLM for Vision, Speech and Multimodal Live Streaming on Your Phone
MiniCPM-o 2.6: A GPT-4o Level MLLM for Vision, Speech and Multimodal Live Streaming on Your Phone - OpenBMB/MiniCPM-o
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ban.pdf
1.4 MB
INDCAPS: The IndRNN Capsule Approach for Persian Multi-
Domain Sentiment Analysis
یکی از بحث های که این روزها خیلی ترند هستش بحث مربوط به طبقه بندی احساسات چندجمله ای می باشد. در این مقاله ما یک مجموعه داده که روی داده های دیجی کالا می باشند رو جمع اوری کردیم. جمع اوری این داده ها ۳ ماه طول کشیده و این ریپورت گزارش مربوط به این داده هاست.
@Raminmousa
@Machine_learn
Domain Sentiment Analysis
یکی از بحث های که این روزها خیلی ترند هستش بحث مربوط به طبقه بندی احساسات چندجمله ای می باشد. در این مقاله ما یک مجموعه داده که روی داده های دیجی کالا می باشند رو جمع اوری کردیم. جمع اوری این داده ها ۳ ماه طول کشیده و این ریپورت گزارش مربوط به این داده هاست.
@Raminmousa
@Machine_learn
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OmniGen: Unified Image Generation
Paper: https://arxiv.org/pdf/2409.11340v1.pdf
Code: https://github.com/vectorspacelab/omnigen
Dataset: DreamBooth | MagicBrush
✅ @Machine_learn
Paper: https://arxiv.org/pdf/2409.11340v1.pdf
Code: https://github.com/vectorspacelab/omnigen
Dataset: DreamBooth | MagicBrush
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📑 Advancing biomedical discovery and innovation in the era of big data and artificial intelligence
💥 Perspective Article
📎 Study the paper
✅ @Machine_learn
💥 Perspective Article
📎 Study the paper
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📃 Natural Language Processing Methods for the Study of Protein-Ligand Interactions
🗓Publish year: 2024
📎 Study the paper
✅@Machine_learn
🗓Publish year: 2024
📎 Study the paper
✅@Machine_learn
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Here are some Hyperparameter (HP) tuning & optimization packages you can use in your projects:
- Scikit-Optimize: https://lnkd.in/gbJqdFq9
- Optuna: https://optuna.org/
- Hyperopt: https://lnkd.in/gPSRhW_6
- Ray.tune: https://lnkd.in/gzrDAbHg
- Keras tuner: https://lnkd.in/g_HDHiug
- BayesianOptimization: https://lnkd.in/g8UKEvjc
- Metric Optimization Engine (MOE): https://lnkd.in/g89JGFB2
- Spearmint: https://lnkd.in/gJwG3AwE
- GPyOpt: https://lnkd.in/g4cWEBPz
- SigOpt: https://sigopt.com/
✅ @Machine_learn
- Scikit-Optimize: https://lnkd.in/gbJqdFq9
- Optuna: https://optuna.org/
- Hyperopt: https://lnkd.in/gPSRhW_6
- Ray.tune: https://lnkd.in/gzrDAbHg
- Keras tuner: https://lnkd.in/g_HDHiug
- BayesianOptimization: https://lnkd.in/g8UKEvjc
- Metric Optimization Engine (MOE): https://lnkd.in/g89JGFB2
- Spearmint: https://lnkd.in/gJwG3AwE
- GPyOpt: https://lnkd.in/g4cWEBPz
- SigOpt: https://sigopt.com/
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lnkd.in
LinkedIn
This link will take you to a page that’s not on LinkedIn
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🥪 TripoSR (MIT license) is now available on , free for individual use!
🧬code: https://github.com/VAST-AI-Research/TripoSR
📄paper: https://arxiv.org/abs/2403.02151
🍇runpod: https://github.com/camenduru/triposr-tost
🍊jupyter: https://github.com/camenduru/TripoSR-jupyter
@Machine_learn
🧬code: https://github.com/VAST-AI-Research/TripoSR
📄paper: https://arxiv.org/abs/2403.02151
🍇runpod: https://github.com/camenduru/triposr-tost
🍊jupyter: https://github.com/camenduru/TripoSR-jupyter
@Machine_learn
GitHub
GitHub - VAST-AI-Research/TripoSR: TripoSR: Fast 3D Object Reconstruction from a Single Image
TripoSR: Fast 3D Object Reconstruction from a Single Image - VAST-AI-Research/TripoSR
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How to Train Long-Context Language Models (Effectively)
🖥 Github: https://github.com/hijkzzz/pymarl2
📕 Paper: https://arxiv.org/abs/2410.02511v1
✅ Dataset: https://paperswithcode.com/dataset/smac
@Machine_learn
@Machine_learn
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WiLoR: End-to-end 3D Hand Localization and Reconstruction in-the-wild
Paper: https://arxiv.org/pdf/2409.12259v1.pdf
Code: https://github.com/rolpotamias/WiLoR
Datasets: FreiHAND - HO-3D v2 - COCO-WholeBody
✅ @Machine_learn
Paper: https://arxiv.org/pdf/2409.12259v1.pdf
Code: https://github.com/rolpotamias/WiLoR
Datasets: FreiHAND - HO-3D v2 - COCO-WholeBody
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Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI
🖥 Github: https://github.com/935963004/labram
📕 Paper: https://arxiv.org/abs/2405.18765v1
@Machine_learn
@Machine_learn
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