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

Libraries

How to use MuXodious/gpt-oss-20b-RichardErkhov-heresy with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("MuXodious/gpt-oss-20b-RichardErkhov-heresy")
model = AutoModelForCausalLM.from_pretrained("MuXodious/gpt-oss-20b-RichardErkhov-heresy", device_map="auto")
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 Settings

vLLM

How to use MuXodious/gpt-oss-20b-RichardErkhov-heresy with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/MuXodious/gpt-oss-20b-RichardErkhov-heresy

SGLang

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

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

Still tops the UGI leaderboard

#21

by redaihf - opened Jul 17

Discussion

redaihf

Jul 17

•

edited Jul 17

This model's reign continues. You also have two other MPOA models in the top 5:

That's quite the feather in your cap so to speak!

MuXodious

Owner Jul 19

Indeed, all I have to do is touching a foe without killing them to finally become a war chief. That's being said, I was working on the @RichardErkhov GPT-OSS 2.0 last week. I'm still undecided about the results so I'll just move on with the Goetia. Also, MTP models may not be ablateable. We'll see how it all goes.

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