| 开发人员: | Alexandru Stamate (1) | ||
| 价格: | 免费 | ||
| 排名: | 0 | ||
| 评价: | 0 我要评价 | ||
| 列表: | 0 + 0 | ||
| 积分: | 1 + 8 (4.5) ¡ | ||
| App Store | |||
说明
- Open Textbook Library integration: Browse and import entire textbooks from OTL through the built‑in Explore view; Noema indexes them locally so you can search and retrieve relevant passages on demand.
- Bring your own data: Add personal documents in PDF or EPUB formats, which are embedded and indexed on‑device to power retrieval‑augmented generation.
- Integrated Hugging Face search: Discover and install any quantized model from the Hugging Face hub, no pre‑set list, with one‑tap installation, automatic dependency management and real‑time download progress.
- RAM check and model size helper: A built‑in advisor estimates each model’s memory footprint and shows a badge when it fits your device’s budget; it can also compute the maximum context length that fits in RAM.
- Triple‑backend support: Run models in GGUF, MLX or Liquid AI’s SLM format: a first for mobile LLM apps. This broad compatibility lets you choose between high‑performance quantized models, Apple‑optimised MLX models and Liquid AI’s lightweight SLMs.
- Low‑RAM, high‑knowledge advantage: Noema shifts knowledge into compact datasets rather than bloated weights, allowing bigger knowledge bases on low‑memory devices.
- Advanced settings for power users: Fine‑tune context length, quantization and GPU acceleration; enable tool‑calling for built‑in search and other functions; and customise model parameters for optimal performance.
- Built‑in tool calling and RAG: Use integrated search tools and retrieval‑augmented generation to query your data without hitting context limits.
- Private and offline: All processing happens locally, and your conversations and files never leave the device.
新版变化
- 版本: 1.4
- 已更新:
- Noema is now completely free—unlimited web search and all features are included. FlashAttention and V-cache quantization cut memory use so larger models fit on more devices. You can benchmark any model or optimization to compare prompt-in/s and token/s. Input fields and remote endpoint forms are redesigned for clarity, and our llama.cpp core is updated to the latest upstream.
价格
- 今天: 免费
- 最小值: 免费
- 最大值: 免费
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- 平台: iOS 应用 (1)
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