Instructions to use Anserwise/AWAXIS-Think-27b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Anserwise/AWAXIS-Think-27b with Transformers:

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

pipe = pipeline("text-generation", model="Anserwise/AWAXIS-Think-27b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("Anserwise/AWAXIS-Think-27b")
model = AutoModelForMultimodalLM.from_pretrained("Anserwise/AWAXIS-Think-27b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
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 Anserwise/AWAXIS-Think-27b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Anserwise/AWAXIS-Think-27b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Anserwise/AWAXIS-Think-27b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Anserwise/AWAXIS-Think-27b

SGLang

How to use Anserwise/AWAXIS-Think-27b 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 "Anserwise/AWAXIS-Think-27b" \
    --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": "Anserwise/AWAXIS-Think-27b",
		"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 "Anserwise/AWAXIS-Think-27b" \
        --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": "Anserwise/AWAXIS-Think-27b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Anserwise/AWAXIS-Think-27b with Docker Model Runner:
```
docker model run hf.co/Anserwise/AWAXIS-Think-27b
```

Anserwise commited on Apr 17

Commit

dff8872

verified ·

1 Parent(s): 11d6c91

Update transformers requirement to >=5.5.4 to fix qwen3_5_text loading error

Browse files

Files changed (1) hide show

README.md +14 -2

README.md CHANGED Viewed

@@ -23,6 +23,19 @@ library_name: transformers
 [FINAL-Bench/Darwin-27B-Opus](https://huggingface.co/FINAL-Bench/Darwin-27B-Opus) 기반, 한국어 특화 고품질 SFT를 수행한 추론 모델입니다.
 ## Method
 - **Base Model**: [Darwin-27B-Opus](https://huggingface.co/FINAL-Bench/Darwin-27B-Opus) (Qwen3.5-27B family)
@@ -52,7 +65,7 @@ library_name: transformers
 ## Usage
-> **Requirements**: `transformers >= 4.57.0`
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
@@ -62,7 +75,6 @@ model = AutoModelForCausalLM.from_pretrained(
     "Anserwise/AWAXIS-Think-27b",
     torch_dtype=torch.bfloat16,
     device_map="auto",
-    trust_remote_code=True
 )
 tokenizer = AutoTokenizer.from_pretrained("Anserwise/AWAXIS-Think-27b")

 [FINAL-Bench/Darwin-27B-Opus](https://huggingface.co/FINAL-Bench/Darwin-27B-Opus) 기반, 한국어 특화 고품질 SFT를 수행한 추론 모델입니다.
+> ⚠️ **Requirements / Loading 주의**
+> 이 모델은 `model_type: qwen3_5_text` (Qwen3.5 하이브리드 아키텍처)를 사용합니다.
+> **`transformers >= 5.5.4` 이상** 에서만 정상 로드됩니다.
+>
+> ```bash
+> pip install --upgrade "transformers>=5.5.4"
+> # 또는 최신 개발판
+> pip install "transformers @ git+https://github.com/huggingface/transformers.git@main"
+> ```
+>
+> 구버전 transformers에서 나타나는 `model_type 'qwen3_5_text'를 인식하지 못함` 오류는
+> 라이브러리 미업데이트로 인한 것이며, 위 명령으로 해결됩니다.
 ## Method
 - **Base Model**: [Darwin-27B-Opus](https://huggingface.co/FINAL-Bench/Darwin-27B-Opus) (Qwen3.5-27B family)
 ## Usage
+> **Requirements**: `transformers >= 5.5.4`
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
     "Anserwise/AWAXIS-Think-27b",
     torch_dtype=torch.bfloat16,
     device_map="auto",
 )
 tokenizer = AutoTokenizer.from_pretrained("Anserwise/AWAXIS-Think-27b")