Add NeMo-Speech.cpp GGUF

.gitattributes

@@ -35,3 +35,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 parakeet-ctc-1.1b.nemo filter=lfs diff=lfs merge=lfs -text
 .safetensors filter=lfs diff=lfs merge=lfs -text
+*.gguf filter=lfs diff=lfs merge=lfs -text

README.md

@@ -192,16 +192,38 @@ pip install nemo_toolkit['all']
 
 ## How to Use this Model
 
+There are several ways to use this model. Choose the one that fits your needs.
+
+### Run locally with NeMo-Speech.cpp
+
+[NeMo-Speech.cpp](https://github.com/NVIDIA/NeMo-Speech.cpp) provides a
+lightweight native C++ runtime for local inference with
+this model. After [installing the runtime](https://github.com/NVIDIA/NeMo-Speech.cpp#installation):
+
+```bash
+hf download nvidia/parakeet-ctc-1.1b \
+  parakeet-ctc-1.1b.q8_0.gguf \
+  --local-dir models
+
+nemo-speech transcribe audio.wav \
+  --model models/parakeet-ctc-1.1b.q8_0.gguf
+```
+
+See the [NeMo-Speech.cpp documentation](https://github.com/NVIDIA/NeMo-Speech.cpp)
+for more details.
+
+### NVIDIA NeMo
+
 The model is available for use in the NeMo toolkit [3], and can be used as a pre-trained checkpoint for inference or for fine-tuning on another dataset. Moreover, you can now run Parakeet CTC natively with [Transformers](https://github.com/huggingface/transformers) 🤗.
 
-### Automatically instantiate the model
+#### Automatically instantiate the model
 
 ```python
 import nemo.collections.asr as nemo_asr
 asr_model = nemo_asr.models.EncDecCTCModelBPE.from_pretrained(model_name="nvidia/parakeet-ctc-1.1b")
 ```
 
-### Transcribing using NeMo
+#### Transcribing using NeMo
 First, let's get a sample
 ```
 wget https://dldata-public.s3.us-east-2.amazonaws.com/2086-149220-0033.wav

parakeet-ctc-1.1b.q8_0.gguf

@@ -0,0 +1,3 @@
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