| File | Size | SHA-256 |
|---|---|---|
canary-qwen.gguf | 4881.9 MB | 73b389d0c65c7e3ce714813c658ac8b421fbaff185ed20b164c589bf30a8d344 |
1# Download (any HTTP client works — the file is a plain GGUF)
2curl -L -o canary-qwen.gguf \
3 https://huggingface.co/vokra/canary-qwen-2.5b/resolve/main/canary-qwen.ggufvokra-cli run --model canary-qwen.gguf --input input.wav| Field | Value |
|---|---|
| Architecture | canary-qwen |
| Tensors | 1686 |
| Upstream source | https://huggingface.co/nvidia/canary-qwen-2.5b |
| Upstream licence | CC-BY-4.0 |
| Licence class | attribution-required |
| Registry model id | nvidia/canary-qwen-2.5b |
| Vokra GGUF schema | 1 |
| Converted by | vokra-core 0.1.0-alpha.0 |
vokra.* metadata, so the card cannot claim something the artifact does not carry.This application uses NVIDIA Canary-Qwen-2.5B (multimodal ASR + LLM: FastConformer encoder + Qwen LM decoder). Model weights are licensed under CC-BY 4.0 (attribution required; commercial use permitted). Copyright (c) NVIDIA. Source: https://huggingface.co/nvidia/canary-qwen-2.5b
vokra_model_attribution (C ABI) and a CLI banner.1shasum -a 256 canary-qwen.gguf
2# expect: 73b389d0c65c7e3ce714813c658ac8b421fbaff185ed20b164c589bf30a8d344