Instructions to use lukey03/Qwen3.5-9B-abliterated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use lukey03/Qwen3.5-9B-abliterated with Transformers:

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

pipe = pipeline("text-generation", model="lukey03/Qwen3.5-9B-abliterated")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("lukey03/Qwen3.5-9B-abliterated")
model = AutoModelForCausalLM.from_pretrained("lukey03/Qwen3.5-9B-abliterated", 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 lukey03/Qwen3.5-9B-abliterated with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "lukey03/Qwen3.5-9B-abliterated"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "lukey03/Qwen3.5-9B-abliterated",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/lukey03/Qwen3.5-9B-abliterated

SGLang

How to use lukey03/Qwen3.5-9B-abliterated 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 "lukey03/Qwen3.5-9B-abliterated" \
    --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": "lukey03/Qwen3.5-9B-abliterated",
		"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 "lukey03/Qwen3.5-9B-abliterated" \
        --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": "lukey03/Qwen3.5-9B-abliterated",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use lukey03/Qwen3.5-9B-abliterated with Docker Model Runner:
```
docker model run hf.co/lukey03/Qwen3.5-9B-abliterated
```

lukey03 commited on Mar 3

Commit

6242e34

verified ·

1 Parent(s): 0935526

Use 9b-prefixed Ollama model names

Browse files

Files changed (1) hide show

README.md +4 -4

README.md CHANGED Viewed

@@ -204,10 +204,10 @@ print(tokenizer.decode(outputs[0], skip_special_tokens=True))
 ```bash
 # Text-only
-ollama run lukey03/qwen3.5-abliterated
 # With vision
-ollama run lukey03/qwen3.5-abliterated-vision
 ```
 Requires **Ollama 0.17.1+**. GGUF files also available at [lukey03/Qwen3.5-9B-abliterated-GGUF](https://huggingface.co/lukey03/Qwen3.5-9B-abliterated-GGUF).
@@ -238,8 +238,8 @@ MLX versions run natively on Apple Silicon (M1/M2/M3/M4) with unified memory —
 | Format | Repo | Size | Best For |
 |--------|------|------|----------|
-| Ollama (text) | `ollama run lukey03/qwen3.5-abliterated` | ~5.2 GB | Easiest setup |
-| Ollama (vision) | `ollama run lukey03/qwen3.5-abliterated-vision` | ~6.1 GB | Easiest setup with vision |
 | Safetensors (F32) | [lukey03/Qwen3.5-9B-abliterated](https://huggingface.co/lukey03/Qwen3.5-9B-abliterated) | ~17 GB | Fine-tuning, full precision inference |
 | GGUF Q4_K_M | [lukey03/Qwen3.5-9B-abliterated-GGUF](https://huggingface.co/lukey03/Qwen3.5-9B-abliterated-GGUF) | ~5.2 GB | llama.cpp, CPU/GPU inference |
 | GGUF Q4_K_M + Vision | [lukey03/Qwen3.5-9B-abliterated-GGUF](https://huggingface.co/lukey03/Qwen3.5-9B-abliterated-GGUF) | ~6.1 GB | Vision GGUF for manual setup |

 ```bash
 # Text-only
+ollama run lukey03/qwen3.5-9b-abliterated
 # With vision
+ollama run lukey03/qwen3.5-9b-abliterated-vision
 ```
 Requires **Ollama 0.17.1+**. GGUF files also available at [lukey03/Qwen3.5-9B-abliterated-GGUF](https://huggingface.co/lukey03/Qwen3.5-9B-abliterated-GGUF).
 | Format | Repo | Size | Best For |
 |--------|------|------|----------|
+| Ollama (text) | `ollama run lukey03/qwen3.5-9b-abliterated` | ~5.2 GB | Easiest setup |
+| Ollama (vision) | `ollama run lukey03/qwen3.5-9b-abliterated-vision` | ~6.1 GB | Easiest setup with vision |
 | Safetensors (F32) | [lukey03/Qwen3.5-9B-abliterated](https://huggingface.co/lukey03/Qwen3.5-9B-abliterated) | ~17 GB | Fine-tuning, full precision inference |
 | GGUF Q4_K_M | [lukey03/Qwen3.5-9B-abliterated-GGUF](https://huggingface.co/lukey03/Qwen3.5-9B-abliterated-GGUF) | ~5.2 GB | llama.cpp, CPU/GPU inference |
 | GGUF Q4_K_M + Vision | [lukey03/Qwen3.5-9B-abliterated-GGUF](https://huggingface.co/lukey03/Qwen3.5-9B-abliterated-GGUF) | ~6.1 GB | Vision GGUF for manual setup |