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Moss Tts v1.5 GGUF

GGUF conversion of OpenMOSS-Team/MOSS-TTS-v1.5 (MossTTSDelay: a Qwen3-8B backbone emitting 32 RVQ audio codebooks under a delay pattern) + its MOSS-Audio-Tokenizer 1.6B transformer codec, for the CrispASR moss-tts...

TipoOtherModelo baseOpenMOSS-Team/MOSS-Audio-TokenizerVersiónMoss tts v1.5 codecBcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
3,31–15,8 GB
Modelo base
OpenMOSS-Team/MOSS-Audio-Tokenizer
Versión
vMoss tts v1.5 codec
Actualizado
28 sept 2026
Fuente
Hugging Face

Descripción de la fuente

MOSS-TTS-v1.5 — GGUF (for CrispASR)

GGUF conversion of OpenMOSS-Team/MOSS-TTS-v1.5 (MossTTSDelay: a Qwen3-8B backbone emitting 32 RVQ audio codebooks under a delay pattern) + its MOSS-Audio-Tokenizer 1.6B transformer codec, for the CrispASR moss-tts backend.

Files

FileWhatSize
moss-tts-v1.5-q4_k.ggufQ4_K backbone (default; audio tables kept F16)~7 GB
moss-tts-v1.5-f16.ggufF16 backbone (needs >20 GB VRAM or CPU; for re-quant)~17 GB
moss-tts-v1.5-codec.ggufF16 transformer codec companion~3.5 GB

Use

crispasr --backend moss-tts -m moss-tts-v1.5-q4_k.gguf \
         --codec-model moss-tts-v1.5-codec.gguf \
         --tts "Hello world." --tts-output out.wav
# or: crispasr --backend moss-tts -m auto --auto-download --tts "..."

Validated on CUDA (P100) by decoded round-trip (synthesize → ASR): the Q4_K backbone produces intelligible, accurate speech end-to-end.

License

Apache-2.0, inherited from the base MOSS-TTS-v1.5 + MOSS-Audio-Tokenizer models (OpenMOSS-Team). This repo redistributes derived GGUF weights under the same terms.

Provenance and EU AI Act Art. 53 note

  • Upstream model: OpenMOSS-Team/MOSS-TTS-v1.5 — published by OpenMOSS-Team.
  • Upstream licence: apache-2.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not.
  • What was done here: format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
  • Training data: documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository. No training-content summary was found on the upstream model card at the time of writing; that documentation gap is upstream's and is not filled here.
  • Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.

Fuentes

1 fuente
Hugging FacePrincipalVersión 75f875ec3cd46cbfa0942a881ec3af85d2ed9b40
huggingface.co/cstr/moss-tts-v1.5-GGUF/tree/75f875ec3cd46cbfa0942a881ec3af85d2ed9b40

Verificado 7 ago

Artefactos del modelo

5 artefactos

moss-tts-v1.5-codec.gguf

gguf · 3,31 GB · SHA-256 9cb5aa788dfb…5382 · Hugging Face

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moss-tts-v1.5-f16.gguf

gguf · 15,8 GB · SHA-256 6da9920aae62…938a · Hugging Face

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moss-tts-v1.5-q4_k.gguf

gguf · 6,52 GB · SHA-256 9e7fb9ed2833…0547 · Hugging Face

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moss-tts-v1.5-q6_k.gguf

gguf · 8,19 GB · SHA-256 5004d550a08c…85e8 · Hugging Face

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moss-tts-v1.5-q8_0.gguf

gguf · 9,75 GB · SHA-256 25a69f762ad6…8ba4 · Hugging Face

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Extractos de fuentes

2 extractos

--- license: apache-2.0 base_model: - OpenMOSS-Team/MOSS-TTS-v1.5 - OpenMOSS-Team/MOSS-Audio-Tokenizer library_name: gguf pipeline_tag: text-to-speech tags: [tts, gguf, crispasr, moss-tts] --- # MOSS-TTS-v1.5 — GGUF (for CrispASR) GGUF conversion of [`OpenMOSS-Team/MOSS-TTS-v1.5`](https://huggingface.co/OpenMOSS-Team/MOSS-TTS-v1.5) (MossTTSDelay: a Qwen3-8B backbone emitting 32 RVQ audio codebooks under a delay pattern) + its [`MOSS-Audio-Tokenizer`](https://huggingface.co/OpenMOSS-Team/MOSS-Audio-Tokenizer) 1.6B transformer codec, for the [CrispASR](https://github.com/CrispStrobe/CrispASR) `moss-tts` backend. ## Files | File | What | Size | |------|------|------| | `moss-tts-v1.5-q4_k.gguf` | Q4_K backbone (default; audio tables kept F16) | ~7 GB | | `moss-tts-v1.5-f16.gguf` | F16 backbone (needs >20 GB VRAM or CPU; for re-quant) | ~17 GB | | `moss-tts-v1.5-codec.gguf` | F16 transformer codec companion | ~3.5 GB | ## Use ```bash crispasr --backend moss-tts -m moss-tts-v1.5-q4_k.gguf \ --codec-model moss-tts-v1.5-codec.gguf \ --tts "Hello world." --tts-output out.wav # or: crispasr --backend moss-tts -m auto --auto-download --tts "..." ``` Validated on CUDA (P100) by decoded round-trip (synthesize → ASR): the Q4_K backbone produces intelligible, accurate speech end-to-end. ## License Apache-2.0, inherited from the base MOSS-TTS-v1.5 + MOSS-Audio-Tokenizer models (OpenMOSS-Team). This repo redistributes derived GGUF weights under the same terms. ## Provenance and EU AI Act Art. 53 note - **Upstream model:** [OpenMOSS-Team/MOSS-TTS-v1.5](https://huggingface.co/OpenMOSS-Team/MOSS-TTS-v1.5) — published by `OpenMOSS-Team`. - **Upstream licence:** `apache-2.0`. This repository redistributes under the same terms; it grants no rights the upstream licence does not. - **What was done here:** format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs. - **Training data:** documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository. No training-content summary was found on the upstream model card at the time of writing; that documentation gap is upstream's and is not filled here. - **Provide...

Source context: 2078 downloads · 0 likes · Pipeline text-to-speech · Library gguf · Repo cstr/moss-tts-v1.5-GGUF