Model Details
Full Model IDhandy-computer/canary-180m-flash-gguf
Pipeline / Taskautomatic-speech-recognition
Librarytranscribe.cpp
Downloads (all-time)312.2K
Likes1
Last Modified10/16/2026
Author / Orghandy-computer
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("automatic-speech-recognition", model="handy-computer/canary-180m-flash-gguf")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transcribe.cppggufasrspeech-to-textcanarymultitask-aedencoder-decodertranslationautomatic-speech-recognitionendeesfrarxiv:2104.02821arxiv:2503.05931arxiv:1706.03762arxiv:2409.13523base_model:nvidia/canary-180m-flashbase_model:quantized:nvidia/canary-180m-flashlicense:cc-by-4.0region:us
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Open on Hugging Face →Browse Model Files ↗← Browse All Models🎙️ Task: Speech Recognition
This model is designed for the Speech Recognition task. Explore more models for this use case.
All Speech Recognition Models →📊 Popularity
⬇ Downloads312.2K
❤️ Community Likes1
🛠️ Requirements
- →Install: pip install transcribe.cpp
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.