| --- |
| 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. |
|
|
