Instructions to use hypaai/Hypa-Orpheus-3b-TTS-VC-ext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use hypaai/Hypa-Orpheus-3b-TTS-VC-ext with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="hypaai/Hypa-Orpheus-3b-TTS-VC-ext")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("hypaai/Hypa-Orpheus-3b-TTS-VC-ext")
model = AutoModelForCausalLM.from_pretrained("hypaai/Hypa-Orpheus-3b-TTS-VC-ext", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use hypaai/Hypa-Orpheus-3b-TTS-VC-ext with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "hypaai/Hypa-Orpheus-3b-TTS-VC-ext"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "hypaai/Hypa-Orpheus-3b-TTS-VC-ext",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/hypaai/Hypa-Orpheus-3b-TTS-VC-ext

SGLang

How to use hypaai/Hypa-Orpheus-3b-TTS-VC-ext with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "hypaai/Hypa-Orpheus-3b-TTS-VC-ext" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "hypaai/Hypa-Orpheus-3b-TTS-VC-ext",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "hypaai/Hypa-Orpheus-3b-TTS-VC-ext" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "hypaai/Hypa-Orpheus-3b-TTS-VC-ext",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Desktop
Docker Model Runner
How to use hypaai/Hypa-Orpheus-3b-TTS-VC-ext with Docker Model Runner:
```
docker model run hf.co/hypaai/Hypa-Orpheus-3b-TTS-VC-ext
```

Hypa-Orpheus-3b-TTS-VC-ext / README.md

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	---
	library_name: transformers
	pipeline_tag: text-generation
	license: apache-2.0
	base_model:
	- hypaai/Hypa-Orpheus-3b-TTS-VC
	datasets:
	- hypaai/Hypa-Voices-snac
	language:
	- en
	- fr
	- es
	- pt
	- ar
	- sw
	- pcm
	- yo
	- ha
	- ig
	- ibb
	- tiv
	- efi
	- anw
	- idc
	- igl
	- nup
	- ego
	- fon
	- urh
	- tw
	- ibr
	tags:
	- orpheus
	- llama
	- text-to-speech
	- voice-cloning
	- speech-synthesis
	- snac
	- multilingual
	- low-resource
	- underrepresented-languages
	- unsloth
	- lora
	- qlora
	- continued-finetuning
	- hypa-ai
	---

	<div align="center">

	![Hypa-Orpheus 3B](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC/resolve/main/Hypa_Orpheus.jpg)

	Extended continued fine-tune of Hypa-Orpheus 3B with a higher-capacity LoRA adapter (r=2048), merged to 16-bit bf16 for inference.

	[![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://www.apache.org/licenses/LICENSE-2.0)
	[![Base: Hypa-Orpheus 3B](https://img.shields.io/badge/Base-Hypa--Orpheus%203B-blue)](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC)
	[![Collection: Hypa-Orpheus](https://img.shields.io/badge/%F0%9F%A4%97%20Collection-Hypa--Orpheus-yellow)](https://huggingface.co/collections/hypaai/hypa-orpheus)
	[![Primary release](https://img.shields.io/badge/Primary-Hypa--Orpheus%203B-green)](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC)
	[![Trained with Unsloth](https://img.shields.io/badge/Trained%20with-Unsloth-orange)](https://github.com/unslothai/unsloth)

	</div>

	## Model Description

	Hypa-Orpheus 3B Extended (`hypaai/Hypa-Orpheus-3b-TTS-VC-ext`) is a continued fine-tune of the production [Hypa-Orpheus 3B](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC) release. It uses the same Hypa-Voices corpus, prompt formats, and SNAC training pipeline as the primary model, but attaches a much higher-rank LoRA adapter (`r=2048`, `α=2048`) on top of the merged Step 3a checkpoint and trains further on the same precomputed integer SNAC shards.

	This is an experimental capacity extension, not a replacement for the primary release. It exists for researchers and deployers who want the strongest held-out loss we observed after continuing training with a larger adapter.

	Collection: [hypaai/hypa-orpheus](https://huggingface.co/collections/hypaai/hypa-orpheus)

	\| Repository \| Role \| Best for \|
	\| --- \| --- \| --- \|
	\| [`hypaai/Hypa-Orpheus-3b-TTS-VC`](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC) \| Primary merged release (r=512, step 44,334) \| Default production deployment \|
	\| `hypaai/Hypa-Orpheus-3b-TTS-VC-ext` (this repo) \| Extended merged release (r=2048, step 4,992) \| Higher-capacity continuation checkpoint \|
	\| [`hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs`](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs) \| Primary LoRA + TensorBoard \| Primary adapter inspection and retraining \|
	\| [`hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext`](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext) \| Extended LoRA + TensorBoard \| Extended adapter inspection and retraining \|

	\| Property \| Primary release \| Extended (this repo) \|
	\| --- \| --- \| --- \|
	\| Starting checkpoint \| `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 size \| ~3.1 GB \| ~12.4 GB \|
	\| Effective batch size \| 96 \| 256 \|
	\| Optimizer steps (shipped) \| 44,334 \| 4,992 \|
	\| Best validation loss \| 3.513 \| 3.438 \|
	\| Approx. validation PPL \| 33.5 \| 31.1 \|

	Capabilities, languages, prompt structure, SNAC decode path, and intended use cases are identical to the primary model. See the main model card for the full description:

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

	---

	## What Changed in This Run

	The extended run kept the same data mixture and response-only SNAC supervision, but increased adapter capacity and batch size while continuing from the already merged production weights:

	\| Hyperparameter \| Primary release \| Extended run \|
	\| --- \| --- \| --- \|
	\| Base weights \| 4-bit QLoRA on Orpheus FT \| Merged bf16 Hypa-Orpheus 3B \|
	\| LoRA rank (r) \| 512 \| 2048 \|
	\| LoRA alpha (α) \| 512 \| 2048 \|
	\| Per-device batch size \| 16 \| 16 \|
	\| Gradient accumulation \| 6 \| 16 \|
	\| Effective batch size \| 96 \| 256 \|
	\| Learning rate \| 5e-5 \| 5e-5 \|
	\| LR schedule \| cosine, 3% warmup \| cosine, 498 warmup steps \|
	\| Optimizer \| AdamW 8-bit \| AdamW 8-bit \|
	\| Weight decay \| 0.01 \| 0.01 \|
	\| Max grad norm \| 1.0 \| 1.0 \|
	\| Eval / save interval \| 2,217 steps \| 832 steps \|
	\| Planned step budget \| 44,334 \| 16,626 \|
	\| Shipped checkpoint \| step 44,334 \| step 4,992 \|
	\| Precision \| bfloat16 \| bfloat16 \|
	\| Random seed \| 3407 \| 3407 \|

	The published extended checkpoint reflects 4,992 optimizer steps, about 30% of one effective epoch on the same interleaved TTS/VC mixture. Training was stopped and released at the validation-best step observed in that continuation segment.

	---

	## Evaluation and Checkpoint Selection

	TensorBoard logs for the extended adapter:

	[Hypa-Orpheus 3B Extended LoRA training logs](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext/tensorboard)

	Headline metrics from the shipped continuation:

	\| 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 \|

	Compared with the primary release validation loss of 3.513 at step 44,334, the extended checkpoint improves held-out loss by 0.075 (approximate validation perplexity 33.5 → 31.1). Validation loss improved at every logged evaluation interval in this continuation.

	\| Step \| Training Loss \| Validation Loss \| Val PPL \| Gen. Gap \|
	\| --- \| --- \| --- \| --- \| --- \|
	\| 832 \| 3.531 \| 3.496 \| 33.0 \| −0.035 \|
	\| 1,664 \| 3.491 \| 3.478 \| 32.4 \| −0.013 \|
	\| 2,496 \| 3.483 \| 3.464 \| 31.9 \| −0.019 \|
	\| 3,328 \| 3.469 \| 3.456 \| 31.7 \| −0.012 \|
	\| 4,160 \| 3.463 \| 3.451 \| 31.5 \| −0.012 \|
	\| 4,992 \| 3.433 \| 3.438 \| 31.1 \| +0.006 \|

	As with the primary release, these scalars measure uncertainty over the supervised target SNAC stream. They do not, by themselves, prove better perceptual quality. The extended checkpoint should be treated as a loss-improved continuation pending formal listening and task benchmarks.

	Gradient norms remained stable throughout the run (roughly 0.18 → 0.11).

	---

	## Which Checkpoint Should I Use?

	\| Use case \| Recommendation \|
	\| --- \| --- \|
	\| Default production \| [`hypaai/Hypa-Orpheus-3b-TTS-VC`](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC) \|
	\| Smaller adapter / full primary training budget \| Primary LoRA repo \|
	\| Lowest published held-out loss after continuation \| This repo (`-ext`) \|
	\| Further high-rank experimentation \| Extended LoRA repo \|

	Choose the primary release when you want the fully budgeted Step 3a training run and the smaller r=512 adapter footprint. Choose this extended release when you want the best validation loss we published after continuing from that checkpoint with a r=2048 adapter, and can accept the larger merged weights and shorter continuation schedule.

	---

	## Quick Start

	### Load the extended merged model

	```python
	from transformers import AutoTokenizer, AutoModelForCausalLM
	import torch

	model_id = "hypaai/Hypa-Orpheus-3b-TTS-VC-ext"

	tokenizer = AutoTokenizer.from_pretrained(model_id)
	model = AutoModelForCausalLM.from_pretrained(
	model_id,
	torch_dtype=torch.bfloat16,
	device_map="auto",
	)
	```

	Prompt assembly, SNAC encode/decode, and vLLM serving follow the same conventions as the primary release. This repository includes the same `handler.py` inference entrypoint pattern as [`hypaai/Hypa-Orpheus-3b-TTS-VC`](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC).

	```bash
	vllm serve hypaai/Hypa-Orpheus-3b-TTS-VC-ext --dtype bfloat16 --max-model-len 4096
	```

	### Load the extended LoRA adapter

	See [`hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext`](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext) for adapter loading, merging, and TensorBoard links.

	---

	## Limitations (Extended Release)

	- Shorter continuation budget. The shipped extended checkpoint covers 4,992 steps, not the full planned 16,626-step schedule.
	- Much larger adapter. r=2048 increases adapter storage and merge size roughly 4× versus the primary release.
	- Experimental status. The primary release remains our default production artifact; this continuation is published for transparency and research comparison.
	- Same perceptual eval gap. Improved held-out loss does not yet come with published WER/CER, speaker-similarity, or MOS results.

	For shared limitations on languages, prompt sensitivity, and context length, see the [primary model card](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC).

	---

	## Released Artifacts

	- Extended merged 16-bit model (this repo): [`hypaai/Hypa-Orpheus-3b-TTS-VC-ext`](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC-ext)
	- Extended LoRA + TensorBoard: [`hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext`](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs-ext)
	- Primary merged release: [`hypaai/Hypa-Orpheus-3b-TTS-VC`](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC)
	- Primary LoRA + TensorBoard: [`hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs`](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC-LoRAs)
	- Training data (public subset): [Hypa-Voices collection](https://huggingface.co/collections/hypaai/hypa-voices)

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

	---

	## Citation

	If you use the extended Hypa-Orpheus checkpoint, please cite both the primary release and this continuation:

	```bibtex
	@misc{hypaorpheus2026,
	title = {Hypa-Orpheus 3B: Multilingual Text-to-Speech and Voice Cloning for Underrepresented Languages},
	author = {{Hypa Intelligence and AfroVoices}},
	year = {2026},
	publisher = {Hugging Face},
	howpublished = {\url{https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC}}
	}

	@misc{hypaorpheus2026ext,
	title = {Hypa-Orpheus 3B Extended: Continued Fine-Tuning with Higher-Capacity LoRA},
	author = {{Hypa Intelligence and AfroVoices}},
	year = {2026},
	publisher = {Hugging Face},
	howpublished = {\url{https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC-ext}}
	}
	```

	---

	## License

	Released under the Apache License 2.0.

	---

	## Acknowledgments

	Same upstream acknowledgments as the [primary Hypa-Orpheus release](https://huggingface.co/hypaai/Hypa-Orpheus-3b-TTS-VC#acknowledgments): Canopy Labs (Orpheus), Meta AI (Llama), Hubert Siuzdak (SNAC), Unsloth, RunPod, Mozilla Common Voice, AfroVoices, and Hypa Intelligence Research (HaIR).

	---

	Hypa Intelligence • [Website](https://hypaintelligence.com) • [Hugging Face](https://huggingface.co/hypaai) • [Updates](https://hypaintelligence.com/updates)