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Model Details
Model Provider
hypaai
Model Tree
hypaai/Hypa-Orpheus-3b-TTS-VC
Input Modalities
Output Modalities
Supported Functionality
| Item | Primary LoRA | Extended (this repo) |
|---|---|---|
| Base model | unsloth/orpheus-3b-0.1-ft | hypaai/Hypa-Orpheus-3b-TTS-VC |
| LoRA rank / alpha | r=512, α=512 | r=2048, α=2048 |
| Trainable parameters | 778M (19.07%) | ~3.11B (~76%) |
| Adapter file size | ~3.1 GB | ~12.4 GB |
| Effective batch size | 96 | 256 |
| Shipped checkpoint | step 44,334 | step 4,992 |
| Best validation loss | 3.513 | 3.438 |
| License | Apache 2.0 | Apache 2.0 |
View extended training logs on Hugging Face
| Metric | Value | Step |
|---|---|---|
| Initial training loss | 3.582 | 1 |
| Final training loss | 3.433 | 4,992 |
| Initial validation loss | 3.496 | 832 |
| Best validation loss (shipped) | 3.438 | 4,992 |
Validation loss improved at every logged interval in this continuation. The merged extended release uses this validation-best adapter at step 4,992.
Primary-run TensorBoard (r=512, 44,334 steps):
hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs/tensorboard
python
from unsloth import FastLanguageModelfrom peft import PeftModelmodel, tokenizer = FastLanguageModel.from_pretrained(model_name="hypaai/Hypa-Orpheus-3b-TTS-VC",max_seq_length=2048,dtype=None,load_in_4bit=True,)model = PeftModel.from_pretrained(model,"hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext",)
Note: the extended adapter was trained with r=2048 on top of the merged primary checkpoint. For continued fine-tuning, initialize a fresh PEFT config with matching rank before loading these weights.
python
model = model.merge_and_unload()model.save_pretrained("Hypa-Orpheus-3b-TTS-VC-ext-merged")tokenizer.save_pretrained("Hypa-Orpheus-3b-TTS-VC-ext-merged")
Or use the pre-merged checkpoint directly:
hypaai/Hypa-Orpheus-3b-TTS-VC-ext
markdown
Hypa-Orpheus-3b-TTS-VC-LoRAs-ext/├── README.md├── adapter_config.json├── adapter_model.safetensors # ~12.4 GB (r=2048)├── training_args.bin└── runs/└── events.out.tfevents.* # TensorBoard scalars
For questions or contributions, contact chris@hypaintelligence.com or open an issue on Hugging Face.