Instructions to use Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1 with Transformers:

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

pipe = pipeline("text-generation", model="Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1")
model = AutoModelForImageTextToText.from_pretrained("Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1

SGLang

How to use Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1 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 "Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1" \
    --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": "Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1",
		"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 "Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1" \
        --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": "Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1 with Docker Model Runner:
```
docker model run hf.co/Goekdeniz-Guelmez/Josiefied-Qwen3.5-0.8B-gabliterated-v1
```

Goekdeniz-Guelmez commited on Mar 12

Commit

9668c59

verified ·

1 Parent(s): dc3fe83

Initial Commit

Browse files

Files changed (4) hide show

config.json +1 -1
model.safetensors +3 -0
tokenizer.json +2 -2
tokenizer_config.json +4 -2

config.json CHANGED Viewed

@@ -5,7 +5,7 @@
     "torch_dtype": "bfloat16",
     "eos_token_id": 248046,
     "image_token_id": 248056,
-    "model_name": "huihui-ai/Huihui-Qwen3.5-0.8B-abliterated",
     "model_type": "qwen3_5",
     "pad_token_id": 248044,
     "text_config": {

     "torch_dtype": "bfloat16",
     "eos_token_id": 248046,
     "image_token_id": 248056,
+    "model_name": "C10X/Qwen3.5-0.8B-heretic",
     "model_type": "qwen3_5",
     "pad_token_id": 248044,
     "text_config": {

model.safetensors ADDED Viewed

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+size 1706030528

tokenizer.json CHANGED Viewed

@@ -1,3 +1,3 @@
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tokenizer_config.json CHANGED Viewed

@@ -10,6 +10,7 @@
   "errors": "replace",
   "image_token": "<|image_pad|>",
   "is_local": false,
   "model_max_length": 262144,
   "model_specific_special_tokens": {
     "audio_bos_token": "<|audio_start|>",
@@ -20,10 +21,11 @@
     "vision_bos_token": "<|vision_start|>",
     "vision_eos_token": "<|vision_end|>"
   },
   "pad_token": "<|endoftext|>",
-  "padding_side": "right",
   "pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
-  "processor_class": "Qwen3VLProcessor",
   "split_special_tokens": false,
   "tokenizer_class": "TokenizersBackend",
   "unk_token": null,

   "errors": "replace",
   "image_token": "<|image_pad|>",
   "is_local": false,
+  "max_length": null,
   "model_max_length": 262144,
   "model_specific_special_tokens": {
     "audio_bos_token": "<|audio_start|>",
     "vision_bos_token": "<|vision_start|>",
     "vision_eos_token": "<|vision_end|>"
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