Instructions to use Kwaipilot/KAT-Coder-V2.5-Dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kwaipilot/KAT-Coder-V2.5-Dev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Kwaipilot/KAT-Coder-V2.5-Dev") 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("Kwaipilot/KAT-Coder-V2.5-Dev") model = AutoModelForMultimodalLM.from_pretrained("Kwaipilot/KAT-Coder-V2.5-Dev", device_map="auto") 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 Kwaipilot/KAT-Coder-V2.5-Dev with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Kwaipilot/KAT-Coder-V2.5-Dev" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Kwaipilot/KAT-Coder-V2.5-Dev", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Kwaipilot/KAT-Coder-V2.5-Dev
- SGLang
How to use Kwaipilot/KAT-Coder-V2.5-Dev 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 "Kwaipilot/KAT-Coder-V2.5-Dev" \ --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": "Kwaipilot/KAT-Coder-V2.5-Dev", "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 "Kwaipilot/KAT-Coder-V2.5-Dev" \ --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": "Kwaipilot/KAT-Coder-V2.5-Dev", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Kwaipilot/KAT-Coder-V2.5-Dev with Docker Model Runner:
docker model run hf.co/Kwaipilot/KAT-Coder-V2.5-Dev
Parser error with claude code w/ or w/o shared template
API Error: 400 Unable to generate parser for this template. Automatic parser generation failed:
While executing CallExpression at line 85, column 32 in source:
...first %}↵ {{- raise_exception('System message must be at the beginnin...
^
Error: Jinja Exception: System message must be at the beginning.
Claude code is unable to respond to any message from this model. Normal chat is okay. don't have the same problem with qwen with or without updated template. Tried both original qwen's template and the one on this repo to no avail.
You can change Line 85 in chat_template.jinja
from
{{- raise_exception('System message must be at the beginning.') }}
into
{{- '<|im_start|>system\n' + content + '<|im_end|>' + '\n' }}
