hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs

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LoRA adapters and TensorBoard logs for Hypa-Orpheus 3B TTS/VC.

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This repository is the LoRA adapter companion to `hypaai/Hypa-Orpheus-3b-TTS-VC`.

Both models belong to the [Hypa-Orpheus collection](https://huggingface.co/collections/hypaai/hypa-orpheus) and describe the same Step 3a production fine-tune. The only difference is what is stored here:

For the full model description, capabilities, prompt format, languages, training data, hyperparameters, evaluation, limitations, citation, and acknowledgements, see the main README:

[hypaai/Hypa-Orpheus-3b-TTS-VC README](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC)

Adapter at a Glance

TensorBoard

Interactive training logs for the production run:

[View TensorBoard on Hugging Face](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs/tensorboard)

Headline metrics from the shipped run:

Validation loss improved at every evaluation interval. The merged release in the sibling repository uses this validation-best checkpoint.

Quick Usage

Load adapters for continued fine-tuning (Unsloth)

from unsloth import FastLanguageModel

model, tokenizer = FastLanguageModel.from_pretrained(
    model_name="unsloth/orpheus-3b-0.1-ft",
    max_seq_length=2048,
    dtype=None,
    load_in_4bit=True,
)

model = FastLanguageModel.get_peft_model(
    model,
    r=512,
    lora_alpha=512,
    target_modules=[
        "q_proj", "k_proj", "v_proj", "o_proj",
        "gate_proj", "up_proj", "down_proj",
    ],
    lora_dropout=0.0,
    bias="none",
    use_gradient_checkpointing="unsloth",
)

# Load the shipped Hypa-Orpheus adapter weights
from peft import PeftModel
model = PeftModel.from_pretrained(model, "hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs")

Merge to 16-bit for inference

After loading the adapter, merge into full weights for deployment (same artifact as the sibling repo):

model = model.merge_and_unload()
model.save_pretrained("Hypa-Orpheus-3b-TTS-VC-merged")
tokenizer.save_pretrained("Hypa-Orpheus-3b-TTS-VC-merged")

For production inference, you can also use the pre-merged checkpoint directly:

hypaai/Hypa-Orpheus-3b-TTS-VC

Repository Contents

Hypa-Orpheus-3b-TTS-VC-LoRAs/
├── README.md
├── adapter_config.json
├── adapter_model.safetensors
├── training_args.bin
└── runs/
    └── events.out.tfevents.*   # TensorBoard scalars

Related Resources

• —Merged model: hypaai/Hypa-Orpheus-3b-TTS-VC
• —Training data (public subset): Hypa-Voices collection
• —Dataset analysis: Hypa-Voices statistical breakdown
• —Upstream base: unsloth/orpheus-3b-0.1-ft

For questions or contributions, contact chris@hypaintelligence.com or open an issue on Hugging Face.