Thursday, 5 November 2026 | التحديث اليومي نظرة ثاقبة للذكاء الاصطناعي، مكتوبة للبناة

AI Hardware, GPUs and Local LLMs — Page 11

Older stories and guides from the Convly archive.

DeepSeek Harne — explained. DeepSeek Harness Launches MIT-Licensed, Every Component a.
الذكاء الاصطناعي الصيني

إطلاق DeepSeek Harness بموجب رخصة معهد ماساتشوستس للتكنولوجيا (MIT)، حيث يُطبَّق كل مكوِّن على شكل إضافية قابلة للتبديل

DeepSeek AI has released the DeepSeek Harness into developer preview, an MIT-licensed agent framework where every component is implemented as a plugin. The release expands DeepSeek’s open-source developer tooling beyond its language models.

10% — measured, not claimed. Hugging Face Datasets.
الدروس التعليمية

Hugging Face Datasets: مرجع المطور

A Hugging Face dataset is a structured data collection hosted on the Hugging Face Hub, searchable at huggingface.co/datasets — over 300,000 public datasets as of 2026. Load any dataset in one line: from datasets import load_dataset; ds = load_dataset(‘stanfordnlp/imdb’)Each dataset ships with typed splits (train/validation/test), a features schema (text, image, audio, labels), and optional streaming for terabyte-scale files. Push your own data with ds.push_to_hub(‘your-username/your-dataset’) after running huggingface-cli login. A Hugging Face dataset is a versioned, structured data collection stored on the Hugging Face Hub and consumed through the datasets Python library.

30% — measured, not claimed. Hugging Face DeepSite.
الدروس التعليمية

Hugging Face DeepSite: مولد تطبيقات الويب أحادية الملف المدعوم بالذكاء الاصطناعي

DeepSite is a free Hugging Face Space athuggingface.co/spaces/enricoros/deepsite that turns a text prompt into a complete, self-contained HTML web app. No installation, no account required to try — open the URL, describe your app, click Generate, get a live preview and a downloadable .html file. The output is a single file with inline CSS and JavaScript; host it on Hugging Face Spaces, GitHub Pages, Netlify, or any static server. Duplicate the Space and add your own Hugging Face API token to avoid queue times and pick your preferred model. Hugging Face DeepSite is an open-source, browser-based web app generator.

100% — measured, not claimed. Ollama Not Using GPU.
الدروس التعليمية

Ollama لا يستخدم GPU: تشخيص وإصلاح الرجوع إلى المعالج

Run ollama ps while a model is loaded — the PROCESSOR column tells you whether Ollama is using GPU or CPU.The most common fix on NVIDIA is installing or updating the host driver so nvidia-smi sees the card, then restarting the Ollama service. If the model is larger than your VRAM, Ollama offloads layers to CPU — use the VRAM calculator to check whether your model fits before downloading it. AMD, Docker, and WSL2 each require platform-specific steps covered below.

4 GB — what it actually needs. llamafile.
الدروس التعليمية

llamafile: تشغيل أي نموذج لغة كملف تنفيذي محمول واحد

llamafile packages a GGUF model and the llama.cpp inference engine into one executable file that runs on Linux, macOS, Windows, FreeBSD, and more — no installation needed. Run ./model.llamafile and a browser chat UI opens automatically; an OpenAI-compatible API is served at http://localhost:8080/v1.Files over 4 GB cannot run directly on Windows — use a smaller quantization or run the runtime and GGUF separately. Best for air-gapped machines, USB deployment, and one-file sharing.

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