Ollama is a free, open source tool that runs large language models locally with a single command, for example ollama run llama3. It manages model downloads, GPU acceleration and a local REST API that most AI applications can talk to. It started as a command line tool and now also ships a simple desktop app with a chat window on Mac and Windows, and it works with many third-party interfaces such as Open WebUI.

Ollama is for developers, tinkerers and anyone who wants a local model as a backend for other software. If you want a full featured chat interface out of the box, LM Studio is more comfortable, but Ollama is lighter and scripts well.

Tiada pemasangan diperlukan - jalankan model AI di awan

BitVector Prism ialah cara paling mudah untuk bermula: pilih model, taip prompt dan jana dalam aplikasi web yang bersih, tanpa apa-apa untuk dikonfigurasi. BitVector juga tersedia di Discord dan di web (SpyGlass).

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Apa yang anda perlukan

macOS 12 or later (Apple Silicon recommended), Windows 10 or 11, or Linux. 8 GB RAM for 7B models, 16 GB for 13B, 32 GB for 33B; an NVIDIA or AMD GPU makes generation much faster. Models take 2 to 40 GB each.

Cara mendapatkan dan memasang Ollama

Download Ollama from ollama.com for Mac or Windows and run the installer, or on Linux run the install script from the site.
Open a terminal (or the Ollama app) and type ollama run llama3.2 (or another model name from the library page); the model downloads and a chat prompt appears.
Browse the model library on ollama.com for Qwen, Gemma, Mistral, DeepSeek, Phi and vision models, each with the exact command to run it.
Optional: install a web interface such as Open WebUI, which connects to Ollama and gives you a ChatGPT-style page in your browser.

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PirateDiffusion hanya di Telegram dan dibina untuk profesional: beribu-ribu model, LoRA dan aliran kerja yang dipacu oleh arahan sembang, dengan penjanaan tanpa had pada pelan harga tetap.

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Cara menggunakan Ollama

Chat in the terminal or the app window; type /bye to exit a terminal chat.
List downloaded models with ollama list, remove one with ollama rm name, and pull a new one with ollama pull name.
Pick a size tag to match your hardware, for example qwen2.5:7b or qwen2.5:14b; smaller tags run on smaller machines.
Use the API at http://localhost:11434 from your own scripts (it is OpenAI compatible), or point apps like Open WebUI, Continue or Zed at it.
Create a custom model with a Modelfile to set a system prompt and parameters, then ollama create myname -f Modelfile.
Vision models (llava, llama3.2-vision, qwen2.5vl) accept images: drag a file into the chat or pass the path in the terminal.

Petua dan masalah biasa

Set OLLAMA_MODELS to move the model folder to a bigger drive.
If the GPU is not used, check that your driver is current; ollama ps shows whether a model runs on GPU or CPU.
Keep the context window (num_ctx) modest unless you need long documents; it has the largest effect on memory.
Ollama can import GGUF files you download yourself through a Modelfile with a FROM line pointing at the file.

Model yang boleh dijalankan dalam Ollama

Ollama runs the open text models under Text / LLM in this catalog that are published in its library or available as GGUF files, which covers Llama, Qwen, Gemma, Mistral, DeepSeek and most others.

Model Text / LLM

Tiada pemasangan diperlukan - jalankan model AI di awan

Tiada GPU, tiada muat turun, tiada Python. Perkhidmatan ini menjalankan model sumber terbuka yang sama pada pelayan mereka sendiri, jadi anda boleh mula menjana dari pelayar, Discord atau Telegram dalam seminit.

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Pautan

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