Text-to-Speech
Transformers
Safetensors
English
moss_tts_nano
feature-extraction
tts
moss-tts-nano
indian-english
lora
voice-cloning
custom_code
Instructions to use IOTEverythin/roxi-tts-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IOTEverythin/roxi-tts-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="IOTEverythin/roxi-tts-v2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("IOTEverythin/roxi-tts-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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fix: gracefully fall back flash_attention_2 -> sdpa when flash_attn not installed
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fix: default attn to sdpa (no flash_attn dependency at inference)
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docs: works on modern transformers now; soften version note
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fix: cross-version transformers compat (resolves list|set crash on modern transformers)
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docs: pin transformers==4.57.1 + fix usage (resolves list|set / missing lm_head on newer transformers)
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roxi-tts-v2: MOSS-TTS-Nano LoRA Indian-English (with IIT-M attribution)
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initial commit
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