Audio-Text-to-Text
Transformers
Safetensors
English
musicflamingo
text2text-generation
audio
speech
sound
music
reasoning
audio understanding
ASR
audio captioning
long-context
audio-language-model
long-audio
timestamp-grounding
instruction-tuned
Instructions to use nvidia/audio-flamingo-next-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/audio-flamingo-next-hf with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSeq2SeqLM processor = AutoProcessor.from_pretrained("nvidia/audio-flamingo-next-hf") model = AutoModelForSeq2SeqLM.from_pretrained("nvidia/audio-flamingo-next-hf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from nvidia/audio-flamingo-next-hf: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/nvidia/audio-flamingo-next-hf/resolve/main/tokenizer.json
- Command line
-
hf download hf://nvidia/audio-flamingo-next-hf/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/nvidia/audio-flamingo-next-hf/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 61c412de025869a66b5829af3d9f6de3ec2e62390e981a19072aa2947aa8477f
- Size of remote file:
- 11.4 MB
- SHA256:
- a64cc913679c6eaf01ba137504e15a55d174d590944fe06f7b3899b2ae82de31
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