Search Results for "jade code source" - Page 5
Sort By:
Showing 110 open source projects for "jade code source"
View related business solutions-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
1
SG2Im
Code for "Image Generation from Scene Graphs", Johnson et al, CVPR 201
sg2im is a research codebase that learns to synthesize images from scene graphs—structured descriptions of objects and their relationships. Instead of conditioning on free-form text alone, it leverages graph structure to control layout and interactions, generating scenes that respect constraints like “person left of dog” or “cup on table.” The pipeline typically predicts object layouts (bounding boxes and masks) from the graph, then renders a realistic image conditioned on those layouts.... -
2
Leanstral
Open-source code agent designed for Lean 4
Leanstral is an open-weight large language model developed by Mistral AI and specifically designed as a code agent for the Lean 4 proof assistant, enabling advanced interaction with formal mathematics and program verification systems. The model is built to understand and generate Lean 4 code, which is used to express complex mathematical constructs as well as formal software specifications. By focusing on theorem proving and formal reasoning, Leanstral represents a specialized direction... -
3
Kimi K2.7 Code
Coding-focused Kimi model for long-horizon agent workflows
Kimi K2.7 Code is a coding-focused agentic model built on Kimi K2.6, designed for long-horizon software engineering, autonomous coding workflows, and complex tool-based execution. It improves end-to-end task completion across real-world programming scenarios while reducing thinking-token usage by about 30% compared with K2.6. Architecturally, it uses a 1T-parameter Mixture-of-Experts design with 32B activated parameters, 61 layers, 384 experts, a 256K-token context window, and a MoonViT... -
4
Hy3
Open code agent for Lean 4 proofs and formal software verification
Leanstral 1.5 119B A6B is an open-source code agent model from Mistral AI designed specifically for Lean 4, a proof assistant used to express and verify complex mathematical objects and formal software specifications. Built as part of the Mistral Small 4 family, it combines multimodal capabilities with an efficient Mixture-of-Experts architecture containing 119B total parameters and 6.5B activated per token. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
5
Leanstral 1.5
Open code agent for Lean 4 proofs and formal software verification
Leanstral 1.5 119B A6B is an open-source code agent model from Mistral AI designed specifically for Lean 4, a proof assistant used to express and verify complex mathematical objects and formal software specifications. Built as part of the Mistral Small 4 family, it combines multimodal capabilities with an efficient Mixture-of-Experts architecture containing 119B total parameters and 6.5B activated per token. -
6
Mellum-4b-base
JetBrains’ 4B parameter code model for completions
Mellum-4b-base is JetBrains’ first open-source large language model designed and optimized for code-related tasks. Built with 4 billion parameters and a LLaMA-style architecture, it was trained on over 4.2 trillion tokens across multiple programming languages, including datasets such as The Stack, StarCoder, and CommitPack. With a context window of 8,192 tokens, it excels at code completion, fill-in-the-middle tasks, and intelligent code suggestions for professional developer tools and IDEs. ... -
7
Nex-N2-mini
Compact agentic model for coding, tools, and productivity tasks
Nex-N2-mini is an open-source agentic model from Nex AGI designed for real-world productivity, coding, tool use, deep research, and terminal-based execution. Built on Qwen3.5-35B-A3B-Base, it offers a lighter latency and deployment profile than Nex-N2-Pro while preserving the core Nex-N2 “Agentic Thinking” framework. This framework unifies requirement understanding, planning, code implementation, environmental feedback, debugging, evaluation, and iteration into a closed loop. ... -
8
Qwable-v1
Agentic coding model combining Opus reasoning and Fable tools
Qwable-v1 is an open-weight agentic coding model created through a chained distillation process based on Qwen3.6-35B-A3B. The model combines two distinct training stages: first, it was fine-tuned on reasoning traces derived from Claude Opus 4.7 to improve structured reasoning, and then further trained on Claude Fable-5 agentic tool-use traces to develop autonomous coding and tool-calling behavior. The result is a 35B Mixture-of-Experts model with only 3B active parameters that can switch... -
9
OpenVLA 7B
Vision-language-action model for robot control via images and text
OpenVLA 7B is a multimodal vision-language-action model trained on 970,000 robot manipulation episodes from the Open X-Embodiment dataset. It takes camera images and natural language instructions as input and outputs normalized 7-DoF robot actions, enabling control of multiple robot types across various domains. Built on top of LLaMA-2 and DINOv2/SigLIP visual backbones, it allows both zero-shot inference for known robot setups and parameter-efficient fine-tuning for new domains. The model... -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
10
wav2vec2-large-xlsr-53-portuguese
Portuguese ASR model fine-tuned on XLSR-53 for 16kHz audio input
wav2vec2-large-xlsr-53-portuguese is an automatic speech recognition (ASR) model fine-tuned on Portuguese using the Common Voice 6.1 dataset. It is based on Facebook’s wav2vec2-large-xlsr-53, a multilingual self-supervised learning model, and is optimized to transcribe Portuguese speech sampled at 16kHz. The model performs well without a language model, though adding one can improve word error rate (WER) and character error rate (CER). It achieves a WER of 11.3% (or 9.01% with LM) on Common...
