Audio-to-Audio
Moshi
Safetensors
Hindi
speech-to-speech
hindi
conversational-ai
audio
full-duplex
duplex-dialogue
indian-languages
Instructions to use JoshTalksAI/Human-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Moshi
How to use JoshTalksAI/Human-1 with Moshi:
# pip install moshi # Run the interactive web server python -m moshi.server --hf-repo "JoshTalksAI/Human-1" # Then open https://localhost:8998 in your browser
# pip install moshi import torch from moshi.models import loaders # Load checkpoint info from HuggingFace checkpoint = loaders.CheckpointInfo.from_hf_repo("JoshTalksAI/Human-1") # Load the Mimi audio codec mimi = checkpoint.get_mimi(device="cuda") mimi.set_num_codebooks(8) # Encode audio (24kHz, mono) wav = torch.randn(1, 1, 24000 * 10) # [batch, channels, samples] with torch.no_grad(): codes = mimi.encode(wav.cuda()) decoded = mimi.decode(codes) - Notebooks
- Google Colab
- Kaggle
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# Human-1: A Full-Duplex Conversational Model for Hindi
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**ποΈ [Try the live demo β](https://ai.joshtalks.com/research/human-1)** | **π [Paper β](https://
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Human-1 by Josh Talks is the first full-duplex spoken dialogue model for Hindi, built by adapting [Kyutai's Moshi](https://github.com/kyutai-labs/moshi) architecture. It enables real-time, natural Hindi conversation with support for interruptions, overlaps, backchannels, and natural turn-taking β trained on 26,000 hours of real spontaneous Hindi conversations from 14,695 speakers.
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# Human-1: A Full-Duplex Conversational Model for Hindi
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**ποΈ [Try the live demo β](https://ai.joshtalks.com/research/human-1)** | **π [Paper β](https://arxiv.org/pdf/2604.23295v1)**
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Human-1 by Josh Talks is the first full-duplex spoken dialogue model for Hindi, built by adapting [Kyutai's Moshi](https://github.com/kyutai-labs/moshi) architecture. It enables real-time, natural Hindi conversation with support for interruptions, overlaps, backchannels, and natural turn-taking β trained on 26,000 hours of real spontaneous Hindi conversations from 14,695 speakers.
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