Instructions to use KRLabsOrg/squeez-2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use KRLabsOrg/squeez-2b with Transformers:

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

pipe = pipeline("text-generation", model="KRLabsOrg/squeez-2b")
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("KRLabsOrg/squeez-2b")
model = AutoModelForImageTextToText.from_pretrained("KRLabsOrg/squeez-2b")
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

vLLM

How to use KRLabsOrg/squeez-2b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "KRLabsOrg/squeez-2b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "KRLabsOrg/squeez-2b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/KRLabsOrg/squeez-2b

SGLang

How to use KRLabsOrg/squeez-2b 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 "KRLabsOrg/squeez-2b" \
    --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": "KRLabsOrg/squeez-2b",
		"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 "KRLabsOrg/squeez-2b" \
        --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": "KRLabsOrg/squeez-2b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use KRLabsOrg/squeez-2b with Docker Model Runner:
```
docker model run hf.co/KRLabsOrg/squeez-2b
```

Add library_name to metadata

by nielsr HF Staff - opened Apr 12

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+21

-12

Files changed (1) hide show

README.md +21 -12

README.md CHANGED Viewed

@@ -1,17 +1,18 @@
 ---
-license: apache-2.0
 language:
 - en
 tags:
 - code
 - tool-output
 - pruning
 - coding-agents
 - extraction
-datasets:
-- KRLabsOrg/tool-output-extraction-swebench
-base_model: Qwen/Qwen3.5-2B
-pipeline_tag: text-generation
 thumbnail: https://raw.githubusercontent.com/KRLabsOrg/squeez/main/assets/squeez_mascot.png
 ---
@@ -115,11 +116,18 @@ messages = [
         "Do not rewrite, summarize, or invent lines."
     )},
     {"role": "user", "content": (
-        "<query>\nFind the failing authentication test\n</query>\n"
-        "<tool_output>\n"
-        "PASSED tests/test_login.py::test_valid_credentials\n"
-        "FAILED tests/test_login.py::test_token_refresh - AssertionError: expected 200 got 401\n"
-        "PASSED tests/test_login.py::test_logout\n"
         "</tool_output>"
     )},
 ]
@@ -141,7 +149,8 @@ print(response)
 **Input** — Chat messages with system prompt:
 - System: extraction instructions (see above)
-- User: `<query>{task}</query>\n<tool_output>{raw_output}</tool_output>`
 **Output** — Verbatim lines in XML tags:
 ```
@@ -205,4 +214,4 @@ Apache 2.0
       primaryClass={cs.SE},
       url={https://arxiv.org/abs/2604.04979},
 }
-```

 ---
+base_model: Qwen/Qwen3.5-2B
+datasets:
+- KRLabsOrg/tool-output-extraction-swebench
 language:
 - en
+license: apache-2.0
+pipeline_tag: text-generation
+library_name: transformers
 tags:
 - code
 - tool-output
 - pruning
 - coding-agents
 - extraction
 thumbnail: https://raw.githubusercontent.com/KRLabsOrg/squeez/main/assets/squeez_mascot.png
 ---
         "Do not rewrite, summarize, or invent lines."
     )},
     {"role": "user", "content": (
+        "<query>
+Find the failing authentication test
+</query>
+"
+        "<tool_output>
+"
+        "PASSED tests/test_login.py::test_valid_credentials
+"
+        "FAILED tests/test_login.py::test_token_refresh - AssertionError: expected 200 got 401
+"
+        "PASSED tests/test_login.py::test_logout
+"
         "</tool_output>"
     )},
 ]
 **Input** — Chat messages with system prompt:
 - System: extraction instructions (see above)
+- User: `<query>{task}</query>
+<tool_output>{raw_output}</tool_output>`
 **Output** — Verbatim lines in XML tags:
 ```
       primaryClass={cs.SE},
       url={https://arxiv.org/abs/2604.04979},
 }
+```