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
Add evaluation results
#8
by SaylorTwift HF Staff - opened
Add .eval_results/A.X-K1.yaml with benchmark results from the model card
Thanks for the contribution! The eval results YAML matches the numbers on our model card, so merging this in. Appreciated!
singleheart changed pull request status to merged
No issues!! This is actually part of a new feature named community evals. Your models now appears on the leaderboards on the hub. Here are the docs about it. It would be lovely to have those eval-results in the models for your next model releases 💟