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

Libraries

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

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("HelloTestUser/gpt-oss-20b")
model = AutoModelForCausalLM.from_pretrained("HelloTestUser/gpt-oss-20b")
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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

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

Install from pip and serve model

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

Use Docker

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

SGLang

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

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

dkundel-openai commited on Aug 26, 2025

Commit

6cee5e8

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1 Parent(s): d666cf3

Update README.md

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@@ -13,7 +13,7 @@ tags:
 <p align="center">
   <a href="https://gpt-oss.com"><strong>Try gpt-oss</strong></a> ·
   <a href="https://cookbook.openai.com/topic/gpt-oss"><strong>Guides</strong></a> ·
-  <a href="https://openai.com/index/gpt-oss-model-card"><strong>Model card</strong></a> ·
   <a href="https://openai.com/index/introducing-gpt-oss/"><strong>OpenAI blog</strong></a>
 </p>
@@ -166,3 +166,17 @@ The gpt-oss models are excellent for:
 Both gpt-oss models can be fine-tuned for a variety of specialized use cases.
 This smaller model `gpt-oss-20b` can be fine-tuned on consumer hardware, whereas the larger [`gpt-oss-120b`](https://huggingface.co/openai/gpt-oss-120b) can be fine-tuned on a single H100 node.

 <p align="center">
   <a href="https://gpt-oss.com"><strong>Try gpt-oss</strong></a> ·
   <a href="https://cookbook.openai.com/topic/gpt-oss"><strong>Guides</strong></a> ·
+  <a href="https://arxiv.org/abs/2508.10925"><strong>Model card</strong></a> ·
   <a href="https://openai.com/index/introducing-gpt-oss/"><strong>OpenAI blog</strong></a>
 </p>
 Both gpt-oss models can be fine-tuned for a variety of specialized use cases.
 This smaller model `gpt-oss-20b` can be fine-tuned on consumer hardware, whereas the larger [`gpt-oss-120b`](https://huggingface.co/openai/gpt-oss-120b) can be fine-tuned on a single H100 node.
+# Citation
+```bibtex
+@misc{openai2025gptoss120bgptoss20bmodel,
+      title={gpt-oss-120b & gpt-oss-20b Model Card},
+      author={OpenAI},
+      year={2025},
+      eprint={2508.10925},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2508.10925},
+}
+```