Text Generation
Transformers
Safetensors
English
k2_horizon
k2-horizon
375b
Mixture of Experts
open-weights
ifm
conversational
custom_code
Instructions to use IFM/K2-Horizon-375B-A23B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IFM/K2-Horizon-375B-A23B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="IFM/K2-Horizon-375B-A23B", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("IFM/K2-Horizon-375B-A23B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use IFM/K2-Horizon-375B-A23B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "IFM/K2-Horizon-375B-A23B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "IFM/K2-Horizon-375B-A23B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/IFM/K2-Horizon-375B-A23B
- SGLang
How to use IFM/K2-Horizon-375B-A23B 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 "IFM/K2-Horizon-375B-A23B" \ --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": "IFM/K2-Horizon-375B-A23B", "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 "IFM/K2-Horizon-375B-A23B" \ --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": "IFM/K2-Horizon-375B-A23B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use IFM/K2-Horizon-375B-A23B with Docker Model Runner:
docker model run hf.co/IFM/K2-Horizon-375B-A23B
About the paper
#5
by Hyufg - opened
Hello, IFM team. Will this series of models have their training details open-sourced like the K2 series?
Yes. As we promised, we will be putting out the supporting assets first. Since this time we have many models all at once, the full paper may take me a while.
thank you, nice work !!!