Text Generation
Transformers
Safetensors
English
Korean
AXK1
conversational
custom_code
Eval Results
Instructions to use skt/A.X-K1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use skt/A.X-K1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="skt/A.X-K1", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("skt/A.X-K1", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use skt/A.X-K1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "skt/A.X-K1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "skt/A.X-K1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/skt/A.X-K1
- SGLang
How to use skt/A.X-K1 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 "skt/A.X-K1" \ --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": "skt/A.X-K1", "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 "skt/A.X-K1" \ --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": "skt/A.X-K1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use skt/A.X-K1 with Docker Model Runner:
docker model run hf.co/skt/A.X-K1
Clarification on Post MLP Normalization
#7
by dungquixote42 - opened
"model-00001-of-00260.safetensors" includes "model.layers.0.post_mlp_layernorm.weight" but "modeling_axk1.py" seems to indicate normalization is applied on MoE layers, which is layer 1 and onward.
Is "model.layers.0.post_mlp_layernorm.weight" a placeholder?
Yes, that parameter is effectively an identity op.
It can be considered a placeholder for consistency, and it is not functionally used for layer 0.
We plan to remove it in the next release.
singleheart changed discussion status to closed