Text Generation
Transformers
Safetensors
qwen3_5
qwen3.5
korean
reasoning
thinking
sft
k-ai
conversational
Instructions to use Anserwise/AWAXIS-Think-27b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("Anserwise/AWAXIS-Think-27b") model = AutoModelForCausalLM.from_pretrained("Anserwise/AWAXIS-Think-27b", device_map="auto") 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=256) 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
Commit History
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Fix: Use model_type qwen3_5 (broader transformers compat) for K-AI leaderboard
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Fix: Convert from multimodal wrapper to pure Qwen3.5 language model (K-AI leaderboard compat)
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Add missing processor_config.json
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Add missing video_preprocessor_config.json
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Add missing preprocessor_config.json for vLLM compat
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Fix tokenizer_class: TokenizersBackend -> Qwen2Tokenizer (match Darwin-27B base)
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Fix config: restore qwen3_5 wrapper structure (model.language_model.* weight namespace requires ForConditionalGeneration wrapper)
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Update transformers requirement to >=5.5.4 to fix qwen3_5_text loading error
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Update README
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Initial release
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initial commit
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