Whisper Base GGUF

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-base.bin: native F16 model for whisper.cpp
• Download size: approximately 148 MB
• Best for: a lightweight balance of speed and transcription quality

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

whisper-cli -m whisper-base.bin -f audio.wav

Integrity

• Source model.safetensors SHA-256: 07cadb9f25677c8d50df603e66a98fbd842cce45047139baeb16e6219a1e807b
• Converted model SHA-256: c2dad44135a48bc7c5a93564f4cd5cc8735ba8822999e358eb31f28d14d72a8b
• Conversion tool: ggml-org/whisper.cpp commit 080bbbe85230f624f0b52127f1ae1218247989f9

The converted model was loaded by whisper.cpp and passed an end-to-end transcription test.

--- base_model: unslothai/whisper-base license: apache-2.0 library_name: whisper.cpp pipeline_tag: automatic-speech-recognition tags: - whisper - whisper.cpp - ggml - f16 - unsloth-studio - unsloth --- # Whisper Base F16 for Unsloth Studio Run fast, fully local speech-to-text dictation in [Unsloth Studio](https://unsloth.ai/docs). Whisper Base is a lightweight step up from Tiny and is a strong default when you want quick local dictation with better transcription quality. ## 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 Base**. 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-base.bin`: native F16 model for `whisper.cpp` - Download size: approximately 148 MB - Best for: a lightweight balance of speed and transcription quality `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-base.bin -f audio.wav ``` ## Integrity - Source `model.safetensors` SHA-256: `07cadb9f25677c8d50df603e66a98fbd842cce45047139baeb16e6219a1e807b` - Converted model SHA-256: `c2dad44135a48bc7c5a93564f4cd5cc8735ba8822999e358eb31f28d14d72a8b` - Conversion tool: `ggml-org/whisper.cpp` commit `080bbbe85230f624f0b52127f1ae1218247989f9` The converted model was loaded by `whisper.cpp` and passed an end-to-end transcription test.