Audio-to-Audio
Moshi
English
contextspan
full-duplex
spoken-dialogue
speech-to-speech
retrieval
retrieval-augmented-generation
tool-calling
context-spanning
personaplex
Instructions to use mindlogicinc/context-spanning-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Moshi
How to use mindlogicinc/context-spanning-7b with Moshi:
# pip install moshi # Run the interactive web server python -m moshi.server --hf-repo "mindlogicinc/context-spanning-7b" # 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("mindlogicinc/context-spanning-7b") # 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
Download context_spanning_7b.pt from mindlogicinc/context-spanning-7b: direct link, hf CLI and curl.
- Browser
- Download file 16.7 GB
-
https://huggingface.co/mindlogicinc/context-spanning-7b/resolve/main/context_spanning_7b.pt
- Command line
-
hf download hf://mindlogicinc/context-spanning-7b/context_spanning_7b.pt
-
curl -L -o context_spanning_7b.pt https://huggingface.co/mindlogicinc/context-spanning-7b/resolve/main/context_spanning_7b.pt
16.7 GB
- Xet hash:
- 5f692bedcfe398f2c8e838fd02ae5a16464156a1695c461dc74ffb26a03c785e
- Size of remote file:
- 16.7 GB
- SHA256:
- 32a4dec8ea8feb28d20ce485f0e49a09b118413aaaebdd182379db41cd441fcc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.