Instructions to use IFM/K2-Horizon-32B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IFM/K2-Horizon-32B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="IFM/K2-Horizon-32B", 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-32B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use IFM/K2-Horizon-32B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "IFM/K2-Horizon-32B"
# 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-32B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/IFM/K2-Horizon-32B

SGLang

How to use IFM/K2-Horizon-32B 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-32B" \
    --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-32B",
		"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-32B" \
        --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-32B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use IFM/K2-Horizon-32B with Docker Model Runner:
```
docker model run hf.co/IFM/K2-Horizon-32B
```

desaifan-mbzuai commited on about 17 hours ago

Commit

99ffbe5

verified ·

1 Parent(s): 0ef337d

Fix typo

Browse files

Files changed (1) hide show

README.md +2 -2

README.md CHANGED Viewed

@@ -129,7 +129,7 @@ Some stages, such as SFT, have multiple phases with slight changes to the data m
 | Training stage | Training steps | Training tokens | Sequence length | Purpose |
 | --- | --- | --- | --- | --- |
-| Pretraining — Phase 1 | 1100000 | 22.9T | 8K | Pretraining. |
 | Midtraining — Stage 1 | 55000 | 1.1T | 32K | Context extension. |
 | Midtraining — Stage 2 | 25000 | 498B | 128K | Context extension. |
 | Midtraining — Stage 3 | 5500 | 110B | 512K | Context extension. |
@@ -156,7 +156,7 @@ The tables below list the release artifacts for **K2-Horizon-32B**, their availa
 | Model card | [Hugging Face](https://huggingface.co/IFM/K2-Horizon-32B) | Available | N/A |
 | Training logs | [W&B](https://wandb.ai/llm360/K2-Horizon-32B) | Available | N/A |
 | Blog post | [Blog post](https://ifm.ai/blog/k2/) | Available | N/A |
-| Checkpoints | [Checkpoint inventory](#checkpoint-inventory) | Partial | See details below |
 | Technical report | Not yet available | In Progress | End of September 2026 |
 | Code repository | [GitHub](https://github.com/ifm-ai/xllm) | In Progress | End of September 2026 |

 | Training stage | Training steps | Training tokens | Sequence length | Purpose |
 | --- | --- | --- | --- | --- |
+| Pretraining | 1100000 | 22.9T | 8K | Pretraining. |
 | Midtraining — Stage 1 | 55000 | 1.1T | 32K | Context extension. |
 | Midtraining — Stage 2 | 25000 | 498B | 128K | Context extension. |
 | Midtraining — Stage 3 | 5500 | 110B | 512K | Context extension. |
 | Model card | [Hugging Face](https://huggingface.co/IFM/K2-Horizon-32B) | Available | N/A |
 | Training logs | [W&B](https://wandb.ai/llm360/K2-Horizon-32B) | Available | N/A |
 | Blog post | [Blog post](https://ifm.ai/blog/k2/) | Available | N/A |
+| Checkpoints | [Checkpoint inventory](#checkpoint-inventory) | Available | See details below |
 | Technical report | Not yet available | In Progress | End of September 2026 |
 | Code repository | [GitHub](https://github.com/ifm-ai/xllm) | In Progress | End of September 2026 |