Text-to-Speech
Transformers
Safetensors
Qwen3-TTS
English
text-generation
tts
qwen
qwen3
qwen3-tts
voice-design
merged-lora
fine-tuned
audio
Instructions to use handsometiger0202/f-llm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use handsometiger0202/f-llm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="handsometiger0202/f-llm")# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("handsometiger0202/f-llm", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| license: cc-by-nc-sa-4.0 | |
| base_model: macminix/qwen3_voice_design_t1 | |
| pipeline_tag: text-to-speech | |
| library_name: transformers | |
| language: | |
| - en | |
| tags: | |
| - tts | |
| - qwen | |
| - qwen3 | |
| - qwen3-tts | |
| - voice-design | |
| - merged-lora | |
| - fine-tuned | |
| - audio | |
| # ckpt-600 β merged | |
| Self-contained snapshot of [`macminix/qwen3_voice_design_t1`](https://huggingface.co/macminix/qwen3_voice_design_t1) | |
| with the **ckpt-600** LoRA adapter folded into the Talker weights. | |
| No PEFT layers at runtime β load directly with `Qwen3TTSModel.from_pretrained`. | |
| ## Quick start | |
| ```python | |
| from qwen_tts import Qwen3TTSModel | |
| wrap = Qwen3TTSModel.from_pretrained("<this-repo-id>") | |
| wavs, sr = wrap.generate_voice_design( | |
| text="Hello, this is a test.", | |
| instruct="A young adult female speaker speaks calmly at a normal pace.", | |
| language="english", | |
| temperature=0.9, top_p=1.0, top_k=50, | |
| repetition_penalty=1.05, max_new_tokens=600, | |
| ) | |
| ``` | |
| ## Repository layout | |
| Same shape as the upstream macminix repo: | |
| - `config.json`, `model.safetensors` β Qwen3-TTS Talker + Code Predictor (merged) | |
| - `speech_tokenizer/` β 12.5 fps Γ 16 codebook neural codec (unchanged) | |
| - `tokenizer.*`, `vocab.json`, `merges.txt`, `added_tokens.json`, | |
| `special_tokens_map.json` β Qwen2 BPE tokenizer | |
| - `generation_config.json`, `preprocessor_config.json` | |
| - `vocence_config.yaml`, `chute_config.yml` β runtime + Chutes deploy hints | |
| You can drop your own `miner.py` into this repo (same contract as macminix's: | |
| class `Miner` with `__init__(path_hf_repo: Path)`, `warmup()`, | |
| `generate_wav(instruction, text)` β `(np.ndarray, int)`); the standard | |
| Vocence chute wrapper will load this model unchanged. | |
| ## Provenance | |
| See [`merge_info.json`](merge_info.json) for the exact base path, adapter | |
| path, LoRA hyperparameters, and merge timestamp. | |