Search Results for "assistant" - Page 27
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Showing 661 open source projects for "assistant"
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Qwen2.5-14B-Instruct
Powerful 14B LLM with strong instruction and long-text handling
...It’s resilient to varied prompt styles and is especially effective for JSON and tabular data generation. The model is instruction-tuned and supports chat templating, making it ideal for chatbot and assistant use cases. -
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Assistant which creates a dot deb package from any windows application installed (and working...) on linux via wine. WiDePaC stands for Wine Debian Package Creator
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Home4Money application is your personal money management assistant. You can work with you budget, arrange loans and accounts.
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MyLib is a smart desktop assistant to manage PDF/PPT/PS documents. These types of documents are frequently used by academic & engineering communities.
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Gemopus
Stable fine-tuned Gemma model for structured, clear responses
...It also strengthens technical explanations, balancing rigor with accessibility. While not intended as a production-ready system, it serves as a high-quality local assistant for structured writing, summarization, and coding tasks. Limitations include potential hallucinations in complex domains and weaker performance compared to larger frontier models. -
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Hermes 4
Hermes 4 FP8: hybrid reasoning Llama-3.1-405B model by Nous Research
...The model is designed for schema adherence, producing valid JSON and repairing malformed outputs, making it highly suitable for tool use and function calling. Hermes 4 is engineered for superior steerability with reduced refusal rates, aligning responses to user values while preserving assistant quality. It achieves state-of-the-art results on RefusalBench, outperforming both closed and open models in balancing helpfulness with adaptability. -
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Llama-3.2-1B
Llama 3.2–1B: Multilingual, instruction-tuned model for mobile AI
meta-llama/Llama-3.2-1B is a lightweight, instruction-tuned generative language model developed by Meta, optimized for multilingual dialogue, summarization, and retrieval tasks. With 1.23 billion parameters, it offers strong performance in constrained environments like mobile devices, without sacrificing versatility or multilingual support. It is part of the Llama 3.2 family, trained on up to 9 trillion tokens and aligned using supervised fine-tuning, preference optimization, and safety... -
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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. The model uses 128 experts with four active for each token and supports a 256K-token context window, making it suitable for extended formal reasoning and large verification tasks. ... -
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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. The model uses 128 experts with four active for each token and supports a 256K-token context window, making it suitable for extended formal reasoning and large verification tasks. ... -
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Ministral 3 8B Instruct 2512
Compact 8B multimodal instruct model optimized for edge deployment
...It combines an 8.4B-parameter language model with a 0.4B vision encoder, enabling both text reasoning and image understanding. This FP8 instruct-fine-tuned variant is optimized for chat, instruction following, and structured outputs, making it ideal for daily assistant tasks and lightweight agentic workflows. Designed for edge deployment, the model can run on a wide range of hardware and fits locally on a single 12GB GPU, with the option for even smaller quantized configurations. Its multilingual support covers dozens of major languages, allowing it to work across diverse global environments and applications. ... -
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Qwable-v1
Agentic coding model combining Opus reasoning and Fable tools
...The result is a 35B Mixture-of-Experts model with only 3B active parameters that can switch between deep reasoning and agent-style execution depending on the system prompt. In normal conversations, it behaves like a reasoning-focused assistant that generates explicit <think> chains before answering. When configured as an agent, it can emit structured tool-use XML for file editing, shell commands, codebase navigation, and workflow automation. Qwable-v1 is designed specifically for software engineering, code editing, debugging, and autonomous coding workflows.