Instructions to use HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit with Transformers:

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

pipe = pipeline("image-text-to-text", model="HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit")
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, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit")
model = AutoModelForMultimodalLM.from_pretrained("HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit")
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 HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit

SGLang

How to use HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit 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 "HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit" \
    --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": "HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit" \
        --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": "HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Unsloth Studio

How to use HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit",
    max_seq_length=2048,
)

Docker Model Runner
How to use HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit with Docker Model Runner:
```
docker model run hf.co/HMkumbo/blood-donation-qwen3.5-4b-dpo-merged-16bit
```

HMkumbo commited on 7 days ago

Commit

973c5ad

verified ·

1 Parent(s): 84539e8

(Trained with Unsloth)

Browse files

Files changed (6) hide show

.gitattributes +1 -0
chat_template.jinja +10 -0
config.json +115 -0
generation_config.json +10 -0
tokenizer.json +3 -0
tokenizer_config.json +300 -0

.gitattributes CHANGED Viewed

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text

 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

chat_template.jinja ADDED Viewed

	@@ -0,0 +1,10 @@

+{{ 'Below are instructions about blood donation tasks in English or Swahili. Write accurate, helpful responses in the same language as the instruction.' }}{% for message in messages %}{% if message['role'] == 'user' %}{{ '
+### Instruction:
+' + message['content'] }}{% elif message['role'] == 'assistant' %}{{ '
+### Response:
+' + message['content'] + '<|im_end|>' }}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '
+### Response:
+' }}{% endif %}

config.json ADDED Viewed

	@@ -0,0 +1,115 @@

+{
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+    "use_cache": false,
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+    "vision_config": {
+        "deepstack_visual_indexes": [],
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+        "in_channels": 3,
+        "initializer_range": 0.02,
+        "intermediate_size": 4096,
+        "model_type": "qwen3_5",
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+        "num_position_embeddings": 2304,
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+        "patch_size": 16,
+        "spatial_merge_size": 2,
+        "temporal_patch_size": 2
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+}

generation_config.json ADDED Viewed

	@@ -0,0 +1,10 @@

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+  "transformers_version": "5.5.0",
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+  "errors": "replace",
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+    "audio_eos_token": "<|audio_end|>",
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+    "image_token": "<|image_pad|>",
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+  "chat_template": "{{ 'Below are instructions about blood donation tasks in English or Swahili. Write accurate, helpful responses in the same language as the instruction.' }}{% for message in messages %}{% if message['role'] == 'user' %}{{ '\n\n### Instruction:\n' + message['content'] }}{% elif message['role'] == 'assistant' %}{{ '\n\n### Response:\n' + message['content'] + '<|im_end|>' }}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '\n\n### Response:\n' }}{% endif %}"
+}