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README.md

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 # TANGO: Text to Audio using iNstruction-Guided diffusiOn
 
-**TANGO** is a latent diffusion model for text to audio generation. **TANGO** can generate realistic audios including human sounds, animal sounds, natural and artificial sounds and sound effects from textual prompts. We use the frozen instruction-tuned LLM Flan-T5 as the text encoder and train a UNet based diffusion model for audio generation. We outperform current state-of-the-art models for audio generation across both objective and subjective metrics. We release our model, training, inference code and pre-trained checkpoints for the research community.
+**TANGO** is a latent diffusion model for text-to-audio generation. **TANGO** can generate realistic audios including human sounds, animal sounds, natural and artificial sounds and sound effects from textual prompts. We use the frozen instruction-tuned LLM Flan-T5 as the text encoder and train a UNet based diffusion model for audio generation. We outperform current state-of-the-art models for audio generation across both objective and subjective metrics. We release our model, training, inference code and pre-trained checkpoints for the research community.
 
-📣 We are inviting collaborators and sponsors to train **TANGO** on larger datasets, like AudioSET
+📣 We are releasing [**Tango-Full-FT**](https://huggingface.co/declare-lab/tango-full-ft) which was first pre-trained on [**TangoPromptBank**](https://huggingface.co/datasets/declare-lab/TangoPromptBank), a collection of diverse text, audio pairs. We later fine tuned this checkpoint on AudioCaps. This checkpoint obtained state-of-the-art results for text-to-audio generation on AudioCaps.
 
 ## Code