Instructions to use niobures/Orpheus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use niobures/Orpheus with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="niobures/Orpheus", filename="bn/Orpheus-bangla-GGUF/Orpheus-bangla.IQ4_XS.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use niobures/Orpheus with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf niobures/Orpheus:Q4_K_M # Run inference directly in the terminal: llama-cli -hf niobures/Orpheus:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf niobures/Orpheus:Q4_K_M # Run inference directly in the terminal: llama-cli -hf niobures/Orpheus:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf niobures/Orpheus:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf niobures/Orpheus:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf niobures/Orpheus:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf niobures/Orpheus:Q4_K_M
Use Docker
docker model run hf.co/niobures/Orpheus:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use niobures/Orpheus with Ollama:
ollama run hf.co/niobures/Orpheus:Q4_K_M
- Unsloth Studio new
How to use niobures/Orpheus 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 niobures/Orpheus 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 niobures/Orpheus to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for niobures/Orpheus to start chatting
- Pi new
How to use niobures/Orpheus with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf niobures/Orpheus:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "niobures/Orpheus:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use niobures/Orpheus with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf niobures/Orpheus:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default niobures/Orpheus:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use niobures/Orpheus with Docker Model Runner:
docker model run hf.co/niobures/Orpheus:Q4_K_M
- Lemonade
How to use niobures/Orpheus with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull niobures/Orpheus:Q4_K_M
Run and chat with the model
lemonade run user.Orpheus-Q4_K_M
List all available models
lemonade list
Orpheus (en)
Browse files- .gitattributes +1 -0
- en/orpheus-3b-0.1-ft/.gitattributes +36 -0
- en/orpheus-3b-0.1-ft/README.md +44 -0
- en/orpheus-3b-0.1-ft/config.json +36 -0
- en/orpheus-3b-0.1-ft/generation_config.json +9 -0
- en/orpheus-3b-0.1-ft/model-00001-of-00004.safetensors +3 -0
- en/orpheus-3b-0.1-ft/model-00002-of-00004.safetensors +3 -0
- en/orpheus-3b-0.1-ft/model-00003-of-00004.safetensors +3 -0
- en/orpheus-3b-0.1-ft/model-00004-of-00004.safetensors +3 -0
- en/orpheus-3b-0.1-ft/model.safetensors.index.json +262 -0
- en/orpheus-3b-0.1-ft/optimizer.bin +3 -0
- en/orpheus-3b-0.1-ft/pytorch_model_fsdp.bin +3 -0
- en/orpheus-3b-0.1-ft/rng_state_0.pth +3 -0
- en/orpheus-3b-0.1-ft/rng_state_1.pth +3 -0
- en/orpheus-3b-0.1-ft/rng_state_2.pth +3 -0
- en/orpheus-3b-0.1-ft/rng_state_3.pth +3 -0
- en/orpheus-3b-0.1-ft/scheduler.pt +3 -0
- en/orpheus-3b-0.1-ft/source.txt +1 -0
- en/orpheus-3b-0.1-ft/special_tokens_map.json +19 -0
- en/orpheus-3b-0.1-ft/tokenizer.json +3 -0
- en/orpheus-3b-0.1-ft/tokenizer_config.json +0 -0
- en/orpheus-3b-0.1-ft/trainer_state.json +0 -0
- en/orpheus-3b-0.1-ft/training_args.bin +3 -0
.gitattributes
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en/orpheus-3b-0.1-ft/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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en/orpheus-3b-0.1-ft/README.md
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---
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library_name: transformers
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language:
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- en
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pipeline_tag: text-to-speech
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license: apache-2.0
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base_model:
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- meta-llama/Llama-3.2-3B-Instruct
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- canopylabs/orpheus-3b-0.1-pretrained
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---
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# Orpheus 3B 0.1 Finetuned
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| 13 |
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**03/18/2025** – We are releasing our 3B Orpheus TTS model with additional finetunes. Code is available on GitHub: [CanopyAI/Orpheus-TTS](https://github.com/canopyai/Orpheus-TTS)
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+
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---
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| 17 |
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| 18 |
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Orpheus TTS is a state-of-the-art, Llama-based Speech-LLM designed for high-quality, empathetic text-to-speech generation. This model has been finetuned to deliver human-level speech synthesis, achieving exceptional clarity, expressiveness, and real-time streaming performances.
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# Model Details
|
| 21 |
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### Model Capabilities
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| 23 |
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- **Human-Like Speech**: Natural intonation, emotion, and rhythm that is superior to SOTA closed source models
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| 25 |
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- **Zero-Shot Voice Cloning**: Clone voices without prior fine-tuning
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| 26 |
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- **Guided Emotion and Intonation**: Control speech and emotion characteristics with simple tags
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- **Low Latency**: ~200ms streaming latency for realtime applications, reducible to ~100ms with input streaming
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### Model Sources
|
| 31 |
+
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- **GitHub Repo:** [https://github.com/canopyai/Orpheus-TTS](https://github.com/canopyai/Orpheus-TTS)
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| 33 |
+
- **Blog Post:** [https://canopylabs.ai/model-releases](https://canopylabs.ai/model-releases)
|
| 34 |
+
- **Colab Inference Notebook:** [notebook link](https://colab.research.google.com/drive/1KhXT56UePPUHhqitJNUxq63k-pQomz3N?usp=sharing)
|
| 35 |
+
- **One-Click Deployment on Baseten:** [https://www.baseten.co/library/orpheus-tts/](https://www.baseten.co/library/orpheus-tts/)
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| 36 |
+
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| 37 |
+
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| 38 |
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# Usage
|
| 39 |
+
|
| 40 |
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Check out our Colab ([link to Colab](https://colab.research.google.com/drive/1KhXT56UePPUHhqitJNUxq63k-pQomz3N?usp=sharing)) or GitHub ([link to GitHub](https://github.com/canopyai/Orpheus-TTS)) on how to run easy inference on our finetuned models.
|
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| 43 |
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# Model Misuse
|
| 44 |
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Do not use our models for impersonation without consent, misinformation or deception (including fake news or fraudulent calls), or any illegal or harmful activity. By using this model, you agree to follow all applicable laws and ethical guidelines. We disclaim responsibility for any use.
|
en/orpheus-3b-0.1-ft/config.json
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{
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"_name_or_path": "canopylabs/orpheus-tts-0.1-pretrained",
|
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"architectures": [
|
| 4 |
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"LlamaForCausalLM"
|
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],
|
| 6 |
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"attention_bias": false,
|
| 7 |
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"attention_dropout": 0.0,
|
| 8 |
+
"bos_token_id": 128000,
|
| 9 |
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"eos_token_id": 128001,
|
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"head_dim": 128,
|
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"hidden_act": "silu",
|
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"hidden_size": 3072,
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"initializer_range": 0.02,
|
| 14 |
+
"intermediate_size": 8192,
|
| 15 |
+
"max_position_embeddings": 131072,
|
| 16 |
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"mlp_bias": false,
|
| 17 |
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"model_type": "llama",
|
| 18 |
+
"num_attention_heads": 24,
|
| 19 |
+
"num_hidden_layers": 28,
|
| 20 |
+
"num_key_value_heads": 8,
|
| 21 |
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"pretraining_tp": 1,
|
| 22 |
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"rms_norm_eps": 1e-05,
|
| 23 |
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"rope_scaling": {
|
| 24 |
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"factor": 32.0,
|
| 25 |
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"high_freq_factor": 4.0,
|
| 26 |
+
"low_freq_factor": 1.0,
|
| 27 |
+
"original_max_position_embeddings": 8192,
|
| 28 |
+
"rope_type": "llama3"
|
| 29 |
+
},
|
| 30 |
+
"rope_theta": 500000.0,
|
| 31 |
+
"tie_word_embeddings": true,
|
| 32 |
+
"torch_dtype": "float32",
|
| 33 |
+
"transformers_version": "4.49.0",
|
| 34 |
+
"use_cache": true,
|
| 35 |
+
"vocab_size": 156940
|
| 36 |
+
}
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en/orpheus-3b-0.1-ft/generation_config.json
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{
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"_from_model_config": true,
|
| 3 |
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"bos_token_id": 128000,
|
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"do_sample": true,
|
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"eos_token_id": 128001,
|
| 6 |
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"temperature": 0.6,
|
| 7 |
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"top_p": 0.9,
|
| 8 |
+
"transformers_version": "4.49.0"
|
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}
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size 4948557560
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en/orpheus-3b-0.1-ft/model-00004-of-00004.safetensors
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