Instructions to use unslothai/whisper-tiny-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- Unsloth Studio
How to use unslothai/whisper-tiny-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for unslothai/whisper-tiny-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for unslothai/whisper-tiny-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for unslothai/whisper-tiny-GGUF to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="unslothai/whisper-tiny-GGUF", max_seq_length=2048, )
Whisper Tiny F16 for Unsloth Studio
Run fast, fully local speech-to-text dictation in Unsloth Studio. Whisper Tiny has the lowest download size and memory use in the default Whisper lineup, making it the fastest option for short everyday dictation.
Run in Unsloth Studio
- Install or update Unsloth Studio.
- Open Settings > Voice.
- Open the local dictation model picker and select Whisper Tiny.
- 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-tiny.bin: native F16 model forwhisper.cpp- Download size: approximately 78 MB
- Best for: fastest startup, lowest memory use, and short dictation
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-tiny.bin -f audio.wav
Integrity
- Source
model.safetensorsSHA-256:7ebd0e69e78190ffe1438491fa05cc1f5c1aa3a4c4db3bc1723adbb551ea2395 - Converted model SHA-256:
bf4711d269a0c0bc7d8411fc2d78d4c6727a215406da46c42975e15684b01746 - Conversion tool:
ggml-org/whisper.cppcommit080bbbe85230f624f0b52127f1ae1218247989f9
The converted model was loaded by whisper.cpp and passed an end-to-end transcription test.
Model tree for unslothai/whisper-tiny-GGUF
Base model
unslothai/whisper-tiny