Downloading models

NobodyWho can either load a model from a path on disk or download it for you on first use, caching it for subsequent runs. This page covers the available model path formats, how to access gated/private models, how to observe a download in progress, and how to inspect what's already in the local cache.

Supported model path formats

The modelPath argument to Model.load, Chat.fromPath, and Model.download accepts:

Form	Example	Notes
HuggingFace reference	hf:owner/repo/file.gguf	Downloaded and cached on first use
llama.cpp-style reference	owner/repo:quantization	Downloaded and cached on first use
HTTPS URL	https://example.com/model.gguf	Downloaded and cached on first use
Local path	./model.gguf	Used as-is

The HuggingFace prefix is case-insensitive and the // is optional — hf:, hf://, huggingface:, and huggingface:// all mean the same thing. Remote models are downloaded to the platform cache directory on first load and re-used on subsequent runs.

The llama.cpp-style reference takes no prefix, and names a HuggingFace repo whose name must end in -GGUF — the convention llama.cpp relies on to work out the filename. NobodyWho resolves it the same way, so ggml-org/gemma-3-1b-it-GGUF:Q8_0 fetches gemma-3-1b-it-Q8_0.gguf from the ggml-org/gemma-3-1b-it-GGUF repo. Both the -GGUF suffix and the quantization are required; without them the string is read as a local path rather than a download. Note: llama.cpp will take the first model in the repo if there is no exact match for the quantization, but NobodyWho will fail with an error if the quantization is not found.

Android permissions

Android requires explicit approval, adding the internet permission to your app's AndroidManifest.xml:

<uses-permission android:name="android.permission.INTERNET" />

NobodyWho does not declare this permission for you, so apps that only load models from local paths keep working without requesting any network access.

Downloading a gated model

Some HuggingFace models are either private or gated by a license that you need to accept. For both scenarios, you need to be authorized to download the model weights.

In that case, you can resort to manually accessing the model page through your web browser, getting the GGUF file downloaded and then pointing our chat instance to the path where you have stored it:

val chat = Chat.fromPath(modelPath = "./model.gguf")

Or you can use the Model.download function, where you can pass in the authorization token:

import ai.nobodywho.Model
import ai.nobodywho.Chat

val modelPath = Model.download(
    modelPath = "hf://NobodyWho/Qwen_Qwen3-0.6B-GGUF/Qwen_Qwen3-0.6B-Q4_K_M.gguf",
    headers = mapOf("Authorization" to "Bearer your_hf_token")
)

val chat = Chat.fromPath(modelPath = modelPath)

The token can be generated in your account settings.

Tracking download progress

When loading a remote model, pass an onDownloadProgress callback to observe the download. It receives (downloadedBytes, totalBytes) and is not called for cached or local files.

val model = Model.load(
    modelPath = "hf://NobodyWho/Qwen_Qwen3-0.6B-GGUF/Qwen_Qwen3-0.6B-Q4_K_M.gguf"
) { downloaded, total ->
    println("$downloaded / $total bytes")
}

Inspecting the model cache

getCachedModels() returns every .gguf model in NobodyWho's cache directory, paired with its size in bytes. This is the same cache used by Model.download and by Chat.fromPath's hf:// paths.

import ai.nobodywho.getCachedModels

for (model in getCachedModels()) {
    println("${model.path} — ${model.size} bytes")
}