Instructions to use alhusains/gpt-oss-20b-ddx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use alhusains/gpt-oss-20b-ddx with Transformers:

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

pipe = pipeline("text-generation", model="alhusains/gpt-oss-20b-ddx")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("alhusains/gpt-oss-20b-ddx", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use alhusains/gpt-oss-20b-ddx with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "alhusains/gpt-oss-20b-ddx"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "alhusains/gpt-oss-20b-ddx",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/alhusains/gpt-oss-20b-ddx

SGLang

How to use alhusains/gpt-oss-20b-ddx 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 "alhusains/gpt-oss-20b-ddx" \
    --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": "alhusains/gpt-oss-20b-ddx",
		"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 "alhusains/gpt-oss-20b-ddx" \
        --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": "alhusains/gpt-oss-20b-ddx",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use alhusains/gpt-oss-20b-ddx with Docker Model Runner:
```
docker model run hf.co/alhusains/gpt-oss-20b-ddx
```

alhusains commited on Nov 26, 2025

Commit

8aa6e92

1 Parent(s): e5fbf62

Fix model-index metadata

Browse files

Files changed (1) hide show

README.md +4 -1

README.md CHANGED Viewed

@@ -22,15 +22,18 @@ widget:
       differential diagnosis and the most likely diagnosis.
     example_title: Radiology differential diagnosis
 model-index:
-  - name: gpt-oss-20b-eurorad-lora
     results:
       - task:
           type: text-generation
         dataset:
           type: eurorad
         metrics:
           - type: accuracy
             value: 0.8615
 ---
 # **GPT-OSS-20B – Eurorad Radiology Reasoning (LoRA Adapter)**

       differential diagnosis and the most likely diagnosis.
     example_title: Radiology differential diagnosis
 model-index:
+  - name: gpt-oss-20b-ddx
     results:
       - task:
           type: text-generation
+          name: Radiology differential diagnosis
         dataset:
           type: eurorad
+          name: Eurorad radiology cases
         metrics:
           - type: accuracy
             value: 0.8615
+            name: exact-match accuracy
 ---
 # **GPT-OSS-20B – Eurorad Radiology Reasoning (LoRA Adapter)**