Automatic Speech Recognition
Transformers
Safetensors
English
parakeet_tdt
feature-extraction
speech
audio
parakeet
tdt
fastconformer
Instructions to use ai-and-i-project/parakeet-tdt-0.6b-v2-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ai-and-i-project/parakeet-tdt-0.6b-v2-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ai-and-i-project/parakeet-tdt-0.6b-v2-hf")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ai-and-i-project/parakeet-tdt-0.6b-v2-hf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
parakeet-tdt-0.6b-v2 (HuggingFace format)
Unofficial HF-format conversion of
nvidia/parakeet-tdt-0.6b-v2
for use with transformers >= 5.8.dev (AutoModelForTDT).
Upstream only ships the .nemo bundle, and transformers' own
convert_nemo_to_hf.py script doesn't handle v2's 1024-token vocab
(it hardcodes a labels.index("<pad>") assumption that only holds
for v3). This repo is the conversion output with that one-line
fallback applied — see
live-llm-bench/scripts/convert-parakeet-v2-nemo-to-hf.py
for the exact transform. Weights are identical to upstream; only
the packaging is changed.
Usage
from transformers import AutoModelForTDT, AutoProcessor
model_id = "ai-and-i-project/parakeet-tdt-0.6b-v2-hf"
processor = AutoProcessor.from_pretrained(model_id)
model = AutoModelForTDT.from_pretrained(model_id, dtype="auto", device_map="cuda")
License
Inherits cc-by-4.0 from
nvidia/parakeet-tdt-0.6b-v2.
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nvidia/parakeet-tdt-0.6b-v2