Topic: foundational-models Goto Github
Some thing interesting about foundational-models
Some thing interesting about foundational-models
foundational-models,Short course's of deeplearning.ai
User: akshaykumarcp
Home Page: https://www.deeplearning.ai/short-courses/
foundational-models,A collection of medical imaging and machine learning projects, including foundational segmentation models.
User: anishsalvi
foundational-models,Collection of resources on the applications of Large Language Models (LLMs) in Audio AI.
Organization: emulationai
Home Page: https://arxiv.org/abs/2308.12792
foundational-models,Vaayushop Foundational models for Finance & DIY model for corporates
User: generativeai4finance
Home Page: https://www.vaayushop.com/
foundational-models,Google Cloud Medical Imaging ML Development Accelerators
Organization: googlecloudplatform
Home Page: https://cloud.google.com/medical-imaging
foundational-models,In this course navigates through the LLMOps pipeline, enabling you to preprocess training data for supervised fine-tuning and deploy custom Large Language Models (LLMs).
User: ksm26
Home Page: https://www.deeplearning.ai/short-courses/llmops/
foundational-models,This repository is for profiling, extracting, visualizing and reusing generative AI weights to hopefully build more accurate AI models and audit/scan weights at rest to identify knowledge domains for risk(s).
Organization: matlok-ai
Home Page: https://bampe-weights.readthedocs.io/en/latest/
foundational-models,RESTful API for bulk operations on a Tator database on clustered, labeled, localization data. It uses the Python web framework FastAPI.
Organization: mbari-org
foundational-models,MOMENT: A Family of Open Time-series Foundation Models
Organization: moment-timeseries-foundation-model
Home Page: https://moment-timeseries-foundation-model.github.io/
foundational-models,ACM Multimedia 2023 (Oral) - RTQ: Rethinking Video-language Understanding Based on Image-text Model
User: sczwangxiao
foundational-models,👁️ + 💬 + 🎧 = 🤖 Curated list of top foundation and multimodal models! [Paper + Code + Examples + Tutorials]
User: skalskip
foundational-models,We introduce Weight Sharing Attention to improve state representation in Reinforcement Learning. By combining embeddings from different Foundational Models, WSA enhances learning efficiency. Tested on Atari games, it performs on par with advanced methods and addresses issues like out-of-distribution data.
User: sopralapanca
foundational-models,Official repository for "CLIP model is an Efficient Continual Learner".
User: vgthengane
Home Page: https://arxiv.org/abs/2210.03114
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