安裝中文字典英文字典辭典工具!
安裝中文字典英文字典辭典工具!
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- Ollama
Get up and running with large language models
- Ollama
Get up and running with large language models Run Llama 3, Phi 3, Mistral, Gemma 2, and other models Customize and create your own
- Download Ollama on Windows
Download Ollama for Windows While Ollama downloads, sign up to get notified of new updates
- Thinking · Ollama Blog
Ollama now has the ability to enable or disable thinking This gives users the flexibility to choose the model’s thinking behavior for different applications and use cases When thinking is enabled, the output will separate the model’s thinking from the model’s output
- OpenAI compatibility · Ollama Blog
Ollama now has built-in compatibility with the OpenAI Chat Completions API, making it possible to use more tooling and applications with Ollama locally Setup Start by downloading Ollama and pulling a model such as Llama 2 or Mistral: ollama pull llama2 Usage cURL
- Streaming responses with tool calling · Ollama Blog
Ollama now supports streaming responses with tool calling This enables all chat applications to stream content and also call tools in real time Models that support using tools: Qwen 3; Devstral; Qwen2 5 and Qwen2 5-coder; Llama 3 1; Llama 4; and more tool calling models Example of simple tool calling (weather) Example of web search Get started
- Structured outputs · Ollama Blog
Ollama now supports structured outputs making it possible to constrain a model’s output to a specific format defined by a JSON schema The Ollama Python and JavaScript libraries have been updated to support structured outputs Use cases for structured outputs include: Parsing data from documents; Extracting data from images
- Ollamas new engine for multimodal models · Ollama Blog
As more multimodal models are released by major research labs, the task of supporting these models the way Ollama intends became more and more challenging We set out to support a new engine that makes multimodal models first-class citizens, and getting Ollama’s partners to contribute more directly to the community via the GGML tensor library
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