Whisper Small GGUF

--- base_model: unslothai/whisper-small license: apache-2.0 library_name: whisper.cpp pipeline_tag: automatic-speech-recognition tags: - whisper - whisper.cpp - ggml - f16 - unsloth-studio - unsloth --- # Whisper Small F16 for Unsloth Studio Run accurate, fully local speech-to-text dictation in [Unsloth Studio](https://unsloth.ai/docs). Whisper Small provides better transcription quality than Tiny or Base while remaining practical for everyday local dictation. ## Run in Unsloth Studio 1. Install or update [Unsloth Studio](https://unsloth.ai/docs). 2. Open **Settings > Voice**. 3. Open the local dictation model picker and select **Whisper Small**. 4. Let Studio download and cache the model. 5. Use the microphone button in the chat composer to dictate locally. The model runs on your device through `whisper.cpp`. Your recorded audio does not need to be sent to a hosted transcription service. ## Model file - `whisper-small.bin`: native F16 model for `whisper.cpp` - Download size: approximately 488 MB - Best for: improved accuracy with moderate local resource use `whisper.cpp` uses a custom GGML binary format for Whisper. The model file is therefore named `.bin`, not `.gguf`, even though this repository follows the common `-GGUF` repository naming convention. No low-bit quantization was applied. Matrix weights are stored as F16, while tensors that `whisper.cpp` requires in F32 remain F32. ## Manual whisper.cpp usage ```bash whisper-cli -m whisper-small.bin -f audio.wav ``` ## Integrity - Source `model.safetensors` SHA-256: `1d7734884874f1a1513ed9aa760a4f8e97aaa02fd6d93a3a85d27b2ae9ca596b` - Converted model SHA-256: `cfd85d74dc730828cef4e13ae65898d9dc6f695fd00394f4399f7310e73cf505` - Conversion tool: `ggml-org/whisper.cpp` commit `080bbbe85230f624f0b52127f1ae1218247989f9` The converted model was loaded by `whisper.cpp` and passed an end-to-end transcription test.

Source context: 0 downloads · 0 likes · Pipeline automatic-speech-recognition · Library whisper.cpp · Repo unslothai/whisper-small-GGUF