Search Results for "e-office"
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Showing 9 open source projects for "e-office"
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DeepSeek Coder V2
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models
...While the V1 models already targeted strong code understanding and generation, V2 appears to push further in both multilingual support and reasoning in code, likely via architectural enhancements or additional training objectives. The repository provides updated model weights, evaluation results on benchmarks (e.g. HumanEval, MultiPL-E, APPS), and new inference/serving scripts. Compared to the original, DeepSeek-Coder-V2 likely incorporates improved context management, caching strategies, or enhanced infilling capabilities. The project aims to provide a more performant and reliable open-source alternative to closed-source code models, optimized for practical usage in code completion, infilling, and code understanding across English and Chinese codebases. -
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DeepSeek Coder
DeepSeek Coder: Let the Code Write Itself
...Multiple sizes of the model are offered (e.g. 1B, 5.7B, 6.7B, 33B) so users can trade off inference cost vs capability. The repo provides model weights, documentation on training setup, evaluation results on common benchmarks (HumanEval, MultiPL-E, APPS, etc.), and inference tools. -
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DreamCraft3D
Official implementation of DreamCraft3D
DreamCraft3D is DeepSeek’s generative 3D modeling framework / model family that likely extends their earlier 3D efforts (e.g. Shap-E or Point-E style models) with more capability, control, or expression. The name suggests a “dream crafting” metaphor—users probably supply textual or image prompts and generate 3D assets (point clouds, meshes, scenes). The repository includes model code, inference scripts, sample prompts, and possibly dataset preparation pipelines. -
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MiniMax-M2.5
State of the art LLM and coding model
MiniMax-M2.5 is a state-of-the-art foundation model extensively trained with reinforcement learning across hundreds of thousands of real-world environments. It delivers leading performance in coding, agentic tool use, search, and complex office workflows, achieving top benchmark scores such as 80.2% on SWE-Bench Verified and 76.3% on BrowseComp. Designed to reason efficiently and decompose tasks like an experienced architect, M2.5 plans features, structure, and system design before generating code. The model supports full-stack development across web, mobile, and desktop platforms, covering the entire lifecycle from system design to testing and code review. ... -
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5
TN 365 Maia 2026 et Mint-KDE
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VALL-E
PyTorch implementation of VALL-E (Zero-Shot Text-To-Speech)
...In addition, we find VALL-E could preserve the speaker's emotion and acoustic environment of the acoustic prompt in synthesis. -
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Hy4 preview
770B MoE model for coding, research, reasoning, and long-context work
...Hy4-preview supports a native 1M-token context window, allowing it to process large codebases, numerous files, and complex extended workflows. Tencent specifically optimized the model for software engineering, office and financial analysis, game development, and scientific research. -
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Solar Open 2
Efficient 250B MoE model for agents, coding, and long-context work
Solar Open 2 is Upstage’s 250B-A15B open-weight large language model designed for agentic workflows, office productivity, document-intensive tasks, coding, and reasoning. Its Hybrid-Attention Mixture-of-Experts architecture contains 250B total parameters while activating only 15B per token, combining three linear-attention layers with one softmax-attention layer for efficient inference. The model supports a native 1M-token context window and uses NoPE instead of rotary positional encoding, reducing long-context KV-cache requirements. ... -
9
fashion-clip
CLIP model fine-tuned for zero-shot fashion product classification
...It supports multilingual fashion queries and works best with clean, product-style images against white backgrounds. The model can be used for product search, recommendation systems, or visual tagging in e-commerce platforms. -
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