Discover Models

Search huggingface.co for GGUF (and safetensors, for vLLM) models directly from the dashboard, see which files will actually fit your GPU before downloading, and pause or resume large transfers.

What it does

The Discover tab queries the Hugging Face Hub API (backend/hub.py search()), filtered to repos tagged gguf, sorted by downloads, last-modified, or likes. Selecting a repo lists its individual GGUF files (hub.py files()), which collapses multi-shard files (*-00001-of-0000N.gguf) into a single entry with their combined size, and separates out mmproj (multimodal projector) files for vision models.

Each file is rated against your machine's total VRAM (all GPUs summed, read from hardware.detect_gpus()). The rating comes from hub.py's _fit():

FITS VRAM — file size × 1.15 is less than or equal to total VRAM. The 15% margin accounts for KV cache and compute buffer headroom on top of the raw weights.
TIGHT — file size fits within total VRAM on its own, but doesn't clear the 1.15× headroom margin. It will load, but there's little room left for context or concurrent requests.
CPU OFFLOAD — file size exceeds total VRAM outright. The model will still load, but part of it runs on system RAM (slower).
? (unknown) — no VRAM was detected (vram_mib is zero or missing), so no rating can be made.

Downloads run in a background thread (hub.py DownloadManager) that streams the file to disk and reports progress the dashboard polls. Pausing keeps the partial .part file on disk; resuming re-issues the request with an HTTP Range header starting from the bytes already downloaded, so a paused multi-gigabyte download picks up where it left off instead of restarting from zero. Cancelling instead deletes the partial file.

Each result also carries platform tags (Windows/Linux/macOS) — GGUF runs on all three via llama.cpp, so GGUF results always show all three; the tag matching your current machine is highlighted.

How to use it

Open the Discover tab. Leave the search box blank to browse the most-downloaded GGUF repos, or type a query (e.g. qwen coder, gemma vision).
Switch the mode dropdown to safetensors (vLLM) if you want a full-precision/quantized model for the vLLM backend instead (Windows + WSL2 only — this option is hidden on platforms without vLLM support).
Click a repo row to expand its file list. Each file shows its size and a fit badge (FITS VRAM / TIGHT / CPU OFFLOAD).
Click Download on the file you want. Progress, current file (for multi-file/shard downloads), speed, and ETA appear in the Download card.
Use Pause to suspend a running download (the partial file is kept) and Resume to continue it later. Cancel download stops it and discards the partial file.
Once a download finishes, click Add to my models to register it as a new section in models.ini, ready to tune and load from the Models tab.

Screenshot

Discover tab

Reference

Concept	Source	Behavior
Search	`backend/hub.py` `search()`	Queries `huggingface.co/api/models?filter=gguf`, sorted by downloads/lastModified/likes.
File listing	`backend/hub.py` `files()`	Lists a repo's `.gguf` files, collapsing sharded files and separating `mmproj` files.
VRAM-fit rating	`backend/hub.py` `_fit()`	`fits`: size × 1.15 ≤ total VRAM. `tight`: size ≤ total VRAM (but not fits). `offload`: size > total VRAM. `unknown`: no VRAM detected.
Download engine	`backend/hub.py` `DownloadManager`	Background thread; one job at a time; progress polled via `/api/hub/progress`.
Pause / resume	`DownloadManager.pause()` / `resume()`	Pause keeps the `.part` file; resume continues via an HTTP `Range` request from the bytes already on disk.
Cancel	`DownloadManager.cancel()`	Stops the job and deletes the partial `.part` file.
Platform tags	`hub.py` `PLATFORMS` / `web/js/discover.js` `platTags()`	GGUF always tags `windows`/`linux`/`macos`; the tag matching the current machine is highlighted.

Troubleshooting

If a search returns an error message instead of results, the request to huggingface.co failed (network issue, or Hugging Face is unreachable) — the error text is shown truncated in the search bar's message area. A GATED tag on a repo means it requires accepting terms and an HF token on huggingface.co first; downloads of gated repos fail without that. Only one download runs at a time — starting a second while one is active is rejected with "A download is already running."

See also Models & Tuning for tuning a model once it's downloaded and added, and models.ini Format for how downloaded models are registered.