اسم المؤلف Mustafa Ihsan

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.

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.

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.

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.

The Hugging Face Inference API — now officially called Inference Providers — routes requests to Groq, Together AI, Fireworks, Cerebras, and others through a single HF token at https://router.huggingface.co/v1.Free tier: $0.10/month in credits for free accounts,$2.00/month for PRO users.

text-generation-webui (widely called oobabooga after its GitHub author) is a free, open-source, browser-based interface for running LLMs locally on your own hardware. Install via one-click scripts — start_windows.bat, start_linux.sh, or start_macos.sh — no manual Python environment setup required. Supports multiple backends: llama.cpp for GGUF files, ExLlamaV2 for EXL2/GPTQ on NVIDIA, and Transformers for HuggingFace models. Includes an OpenAI-compatible API extension (–extensions openai) so other apps can connect to your local model without code changes.