Instructions to use Salesforce/CoDA-v0-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Salesforce/CoDA-v0-Base with Transformers:

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

pipe = pipeline("text-generation", model="Salesforce/CoDA-v0-Base", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Salesforce/CoDA-v0-Base", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Salesforce/CoDA-v0-Base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Salesforce/CoDA-v0-Base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Salesforce/CoDA-v0-Base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Salesforce/CoDA-v0-Base

SGLang

How to use Salesforce/CoDA-v0-Base 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 "Salesforce/CoDA-v0-Base" \
    --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": "Salesforce/CoDA-v0-Base",
		"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 "Salesforce/CoDA-v0-Base" \
        --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": "Salesforce/CoDA-v0-Base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Salesforce/CoDA-v0-Base with Docker Model Runner:
```
docker model run hf.co/Salesforce/CoDA-v0-Base
```

hlnchen

nielsr HF Staff commited on Oct 9, 2025

Commit

54d40e4

verified ·

1 Parent(s): 7bbd0dd

Add `library_name` and update paper link (#3)

Browse files

- Add `library_name` and update paper link (7458eb81916d36acc53bee3e6ab493b8b4539004)

Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

Files changed (1) hide show

README.md +5 -3

README.md CHANGED Viewed

@@ -1,8 +1,9 @@
 ---
-license: cc-by-nc-4.0
 language:
 - en
 pipeline_tag: text-generation
 tags:
 - text diffusion model
 - language model
@@ -15,7 +16,7 @@ tags:
 <p align="center">
   <a href="https://github.com/SalesforceAIResearch/CoDA"><strong>Try CoDA</strong></a> ·
-  <a href="https://github.com/SalesforceAIResearch/CoDA/blob/main/technical_report.pdf"><strong>Technical Report</strong></a> ·
   <a href="https://huggingface.co/collections/Salesforce/coda-68d627d87921c0e28a69e340"><strong>Model Collection</strong></a> ·
   <a href="https://github.com/SalesforceAIResearch/CoDA/blob/main/README.md"><strong>GitHub Repository</strong></a>
 </p>
@@ -197,7 +198,8 @@ Technical report coming soon. For now, please cite:
   title={CoDA: Coding LM via Diffusion Adaptation},
   author={Chen, Haolin and Wang, Shiyu and Qin, Can and Pang, Bo and Liu, Zuxin and Qiu, Jielin and Zhang, Jianguo and Zhou, Yingbo and Chen, Zeyuan and Xu, Ran and Heinecke, Shelby and Savarese, Silvio and Xiong, Caiming and Wang, Huan and Yao, Weiran},
   year={2025},
-  publisher={Salesforce AI Research}
 }
 ```

 ---
 language:
 - en
+license: cc-by-nc-4.0
 pipeline_tag: text-generation
+library_name: transformers
 tags:
 - text diffusion model
 - language model
 <p align="center">
   <a href="https://github.com/SalesforceAIResearch/CoDA"><strong>Try CoDA</strong></a> ·
+  <a href="https://huggingface.co/papers/2510.03270"><strong>Paper</strong></a> ·
   <a href="https://huggingface.co/collections/Salesforce/coda-68d627d87921c0e28a69e340"><strong>Model Collection</strong></a> ·
   <a href="https://github.com/SalesforceAIResearch/CoDA/blob/main/README.md"><strong>GitHub Repository</strong></a>
 </p>
   title={CoDA: Coding LM via Diffusion Adaptation},
   author={Chen, Haolin and Wang, Shiyu and Qin, Can and Pang, Bo and Liu, Zuxin and Qiu, Jielin and Zhang, Jianguo and Zhou, Yingbo and Chen, Zeyuan and Xu, Ran and Heinecke, Shelby and Savarese, Silvio and Xiong, Caiming and Wang, Huan and Yao, Weiran},
   year={2025},
+  publisher={Salesforce AI Research},
+  url={https://huggingface.co/papers/2510.03270}
 }
 ```