Automatic Speech Recognition
Transformers
NeMo
Safetensors
GGUF
PyTorch
parakeet_tdt
feature-extraction
speech
audio
Transducer
Transformer
TDT
FastConformer
Conformer
NeMo
hf-asr-leaderboard
Transformers
Eval Results (legacy)
Eval Results
Instructions to use CollectionStudio/parakeet-tdt-0.6b-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CollectionStudio/parakeet-tdt-0.6b-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="CollectionStudio/parakeet-tdt-0.6b-v3")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("CollectionStudio/parakeet-tdt-0.6b-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from CollectionStudio/parakeet-tdt-0.6b-v3: direct link, hf CLI and curl.
- Browser
- Download file 1.16 MB
-
https://huggingface.co/CollectionStudio/parakeet-tdt-0.6b-v3/resolve/main/tokenizer.json
- Command line
-
hf download hf://CollectionStudio/parakeet-tdt-0.6b-v3/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/CollectionStudio/parakeet-tdt-0.6b-v3/resolve/main/tokenizer.json
1.16 MB
File too large to display, you can check the raw version instead.