Instructions to use ModalityDance/latent-tts-codi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ModalityDance/latent-tts-codi with Transformers:

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

pipe = pipeline("text-generation", model="ModalityDance/latent-tts-codi")

# Load model directly
from transformers import AutoTokenizer, CODIGPT2

tokenizer = AutoTokenizer.from_pretrained("ModalityDance/latent-tts-codi")
model = CODIGPT2.from_pretrained("ModalityDance/latent-tts-codi")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ModalityDance/latent-tts-codi with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ModalityDance/latent-tts-codi"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ModalityDance/latent-tts-codi",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ModalityDance/latent-tts-codi

SGLang

How to use ModalityDance/latent-tts-codi 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 "ModalityDance/latent-tts-codi" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ModalityDance/latent-tts-codi",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "ModalityDance/latent-tts-codi" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ModalityDance/latent-tts-codi",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ModalityDance/latent-tts-codi with Docker Model Runner:
```
docker model run hf.co/ModalityDance/latent-tts-codi
```

dd101bb commited on Jan 11

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@@ -14,7 +14,7 @@ base_model:
 ## Overview
-**CODI** (Continuous Output with Discrete Input) is a latent reasoning model based on GPT-2 that extends the base architecture with an optional projector module for enhanced hidden state representations. This model is part of the [Parallel Test-Time Scaling for Latent Reasoning Models](https://arxiv.org/abs/2510.07745) framework.
 ## Model Details

 ## Overview
+**CODI** (Continuous Chain-of-Thought via Self-Distillation) is a latent reasoning model based on GPT-2 that extends the base architecture with an optional projector module for enhanced hidden state representations. This model is part of the [Parallel Test-Time Scaling for Latent Reasoning Models](https://arxiv.org/abs/2510.07745) framework.
 ## Model Details