Whisper Large v3 GGUF
Run maximum-quality, fully local speech-to-text dictation in Unsloth Studio. Whisper Large v3 is the most accurate option in the default Whisper lineup when transcription quality matters more than download size or speed.
Source du modèle
- Type
- Other
- Taille du fichier
- 2,88 GB
- Modèle de base
- unslothai/whisper-large-v3
- Version
- vWhisper large v3
- Mis à jour
- 26 oct. 2026
- Source
- Hugging Face
Description de la source
Whisper Large v3 F16 for Unsloth Studio
Run maximum-quality, fully local speech-to-text dictation in Unsloth Studio. Whisper Large v3 is the most accurate option in the default Whisper lineup when transcription quality matters more than download size or speed.
Run in Unsloth Studio
- Install or update Unsloth Studio.
- Open Settings > Voice.
- Open the local dictation model picker and select Whisper Large v3.
- Let Studio download and cache the model.
- 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-large-v3.bin: native F16 model forwhisper.cpp- Download size: approximately 3.1 GB
- Best for: highest transcription quality on capable hardware
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-large-v3.bin -f audio.wav
Integrity
- Source
model.safetensorsSHA-256:a8e94b85976e5864ba3e9525c7e6c83b2a1eca42d4b797a0c7c24d778e40fd95 - Converted model SHA-256:
e4fb6f478cfec2e2bbd4b271654338b08492550bbf221361a29d890bc22fbe01 - Conversion tool:
ggml-org/whisper.cppcommit080bbbe85230f624f0b52127f1ae1218247989f9
The converted model was loaded by whisper.cpp and passed an end-to-end transcription test.
Sources
1 source
Sources
1 sourceVérifié 26 oct.
Artefacts du modèle
1 artefact
Artefacts du modèle
1 artefactExtraits de sources
2 extraits
Extraits de sources
2 extraits--- base_model: unslothai/whisper-large-v3 license: apache-2.0 library_name: whisper.cpp pipeline_tag: automatic-speech-recognition tags: - whisper - whisper.cpp - ggml - f16 - unsloth-studio - unsloth --- # Whisper Large v3 F16 for Unsloth Studio Run maximum-quality, fully local speech-to-text dictation in [Unsloth Studio](https://unsloth.ai/docs). Whisper Large v3 is the most accurate option in the default Whisper lineup when transcription quality matters more than download size or speed. ## 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 Large v3**. 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-large-v3.bin`: native F16 model for `whisper.cpp` - Download size: approximately 3.1 GB - Best for: highest transcription quality on capable hardware `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-large-v3.bin -f audio.wav ``` ## Integrity - Source `model.safetensors` SHA-256: `a8e94b85976e5864ba3e9525c7e6c83b2a1eca42d4b797a0c7c24d778e40fd95` - Converted model SHA-256: `e4fb6f478cfec2e2bbd4b271654338b08492550bbf221361a29d890bc22fbe01` - 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-large-v3-GGUF
