Quantized Mistral 7B Instruct models optimized for fast, CPU-only local inference with Ollama. Multiple variants balancing speed, quality, and memory efficiency.
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A domain-aware maritime AI assistant providing practical, high-level guidance across shipping operations, regulations, engineering, safety, and sustainability.
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A general-purpose AI assistant specialized for the maritime and shipping industry, providing practical, domain-aware support across operations, regulations, safety, and logistics.
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Series of 37b-48b experimental models. Made by SteelStorage (Huggingface).
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Description: A compact, efficient model designed for quick responses and resource-constrained environments. Ideal for general conversational AI, basic task automation, and applications requiring fast inference times with minimal computational overhead
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Description: A compact, efficient model designed for quick responses and resource-constrained environments. Ideal for general conversational AI, basic task automation, and applications requiring fast inference times with minimal computational overhead.
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Astria is a multimodal model built by combining a LLaVA vision encoder with the new Ministral model, producing a unified system capable of detailed visual understanding and strong general-purpose reasoning.
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A small multi-agent orchestrator built on Llama3.2 that coordinates LLM agents and tools by outputting "next actions." Use it as the central routing brain in your agentic workflows.
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You are helping me write code for the n8n Code node. Language is JavaScript. Input data structure is: … I want the output to look like: … Return a full snippet that ends with return items; or return [{ json: … }]; and nothing else.
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https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3