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library_name: pytorch
tags:
- bidirectional-flow-matching
- text-to-image
- image-to-text
- text-to-speech
- automatic-speech-recognition
---
# BVFM model weights
This model repository contains the deployment weights for the image/text and
speech/text branches of Bidirectional Variational Flow Matching (BVFM). Source
code, training/inference entry points, and environment instructions live in
the separate GitHub repository.
## Layout
```text
image/
bvfm_image_step40000.pt
FlowTiTok_512.bin
README.md
speech/
bvfm_speech_step299999_inference.pt
merged_config.json
semantic_vae_1000k/
config.json
metainfo.json
dac/ema_state_dict.pth
README.md
```
The repository intentionally excludes training optimizer states, periodic
snapshots, logs, metrics, generated samples, datasets, and caches.
Clone with Git LFS or use `huggingface-cli download`. Point the GitHub code at
the downloaded root with:
```bash
export BVFM_WEIGHTS_ROOT=/path/to/this/model/repository
```
See the branch-specific READMEs for exact file roles and checksums.
## Third-party components
`image/FlowTiTok_512.bin` is the released FlowTiTok image tokenizer required
by image encoding and decoding. `speech/semantic_vae_1000k` is the released
Semantic-VAE decoder required to map the 64-D speech latent to waveform. See
`THIRD_PARTY_NOTICES.md` and retain the corresponding upstream notices when
redistributing these files.
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