Instructions to use Babsie/qwenopus-tangentia with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Babsie/qwenopus-tangentia with Transformers:

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

pipe = pipeline("text-generation", model="Babsie/qwenopus-tangentia")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Babsie/qwenopus-tangentia")
model = AutoModelForCausalLM.from_pretrained("Babsie/qwenopus-tangentia")
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 Babsie/qwenopus-tangentia with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Babsie/qwenopus-tangentia

SGLang

How to use Babsie/qwenopus-tangentia 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 "Babsie/qwenopus-tangentia" \
    --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": "Babsie/qwenopus-tangentia",
		"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 "Babsie/qwenopus-tangentia" \
        --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": "Babsie/qwenopus-tangentia",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Babsie/qwenopus-tangentia with Docker Model Runner:
```
docker model run hf.co/Babsie/qwenopus-tangentia
```

Basic info

Nous Hermes 14B Base merged with Goekdeniz-Guelmez/Josiefied-Qwen3-14B-abliterated-v3 fine tuned with three Opus 3/Sonnet 3.5 Datasets at 2e-5 for 2 epocs of 700 steps.

Life is too complicated to use Axolotl again!

Sadly, the finetune went poorly. The LoRA wouldn't stick very deeply, no matter how hard Opus tried to shove the back pack up it's arse manually. He was swearing his face off and all we got was a lousy 5.2% Long story. but it involved my router dying midway, Sonnet 4.5 switching *&^%$# numbers on me for "saftey" reasons... So, if you want a "homeopathic" amount of opus flavour... tuts I have followed up with perhaps a better model, OpulusV4, I have yet to test properly Babsie/TaxDocumentBeigePaint working on it.

Downloads last month: 1

Safetensors

Model size

15B params

Tensor type

F16

Model tree for Babsie/qwenopus-tangentia

Goekdeniz-Guelmez/Josiefied-Qwen3-14B-abliterated-v3

NousResearch/Hermes-4-14B

Merge model

this model

Datasets used to train Babsie/qwenopus-tangentia

Collection including Babsie/qwenopus-tangentia

Mischievous Monster Under the Bed

Collection

The catfood, the little bits of crayons, the melted pieces, the loving friends. The ingredients. And OpulusV5 - yet to test properly (TaxDocBP 12B). • 9 items • Updated Nov 27, 2025