Instructions to use hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("hypaai/Hypa-Orpheus-3b-TTS-VC") model = PeftModel.from_pretrained(base_model, "hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext", max_seq_length=2048, )
This repository is the extended LoRA companion to hypaai/Hypa-Orpheus-3b-TTS-VC-ext.
It continues training from the merged primary release hypaai/Hypa-Orpheus-3b-TTS-VC with a new, higher-rank adapter (r=2048, α=2048) on the same Hypa-Voices SNAC precompute pipeline.
Collection: hypaai/hypa-orpheus
| Repository | Contents | Best for |
|---|---|---|
hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs |
Primary r=512 adapters | Default adapter inspection / retraining |
hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext (this repo) |
Extended r=2048 adapters | High-capacity continuation experiments |
hypaai/Hypa-Orpheus-3b-TTS-VC |
Primary merged weights | Default inference |
hypaai/Hypa-Orpheus-3b-TTS-VC-ext |
Extended merged weights | Extended inference checkpoint |
For capabilities, prompt format, languages, dataset details, and primary-training context, see:
Adapter at a Glance
| 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%) | |
| 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 |
TensorBoard
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
Quick Usage
Load the extended adapter (Unsloth)
from unsloth import FastLanguageModel
from peft import PeftModel
model, 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.
Merge to 16-bit for inference
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
Repository Contents
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
Related Resources
- Extended merged model: hypaai/Hypa-Orpheus-3b-TTS-VC-ext
- Primary merged model: hypaai/Hypa-Orpheus-3b-TTS-VC
- Primary LoRA adapters: hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs
- Training data (public subset): Hypa-Voices collection
For questions or contributions, contact chris@hypaintelligence.com or open an issue on Hugging Face.
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