Instructions to use IFM/K2-Horizon-0.9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IFM/K2-Horizon-0.9B with Transformers:

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

pipe = pipeline("text-generation", model="IFM/K2-Horizon-0.9B", 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-0.9B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use IFM/K2-Horizon-0.9B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "IFM/K2-Horizon-0.9B"
# 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-0.9B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/IFM/K2-Horizon-0.9B

SGLang

How to use IFM/K2-Horizon-0.9B 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-0.9B" \
    --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-0.9B",
		"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-0.9B" \
        --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-0.9B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use IFM/K2-Horizon-0.9B with Docker Model Runner:
```
docker model run hf.co/IFM/K2-Horizon-0.9B
```

zhou94539 commited on 4 days ago

Commit

aa164f1

verified ·

1 Parent(s): 9ddd29a

Upload config.json to rl-mopd

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config.json +88 -0

config.json ADDED Viewed

	@@ -0,0 +1,88 @@

+{
+  "architectures": [
+    "K2HorizonForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "auto_map": {
+    "AutoConfig": "configuration_k2_horizon.K2HorizonConfig",
+    "AutoModel": "modeling_k2_horizon.K2HorizonModel",
+    "AutoModelForCausalLM": "modeling_k2_horizon.K2HorizonForCausalLM"
+  },
+  "bos_token_id": 0,
+  "decoder_sparse_step": 1,
+  "dtype": "float32",
+  "eos_token_id": 1,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 1536,
+  "initializer_range": 0.02,
+  "intermediate_size": 5120,
+  "layernorm_num_groups": 1,
+  "max_position_embeddings": 131072,
+  "mlp_only_layers": [
+    0,
+    1,
+    2,
+    3,
+    4,
+    5,
+    6,
+    7,
+    8,
+    9,
+    10,
+    11,
+    12,
+    13,
+    14,
+    15,
+    16,
+    17,
+    18,
+    19,
+    20,
+    21,
+    22,
+    23,
+    24,
+    25,
+    26,
+    27
+  ],
+  "model_type": "k2_horizon",
+  "moe_gate_bias": false,
+  "moe_intermediate_size": 0,
+  "norm_topk_prob": true,
+  "num_attention_heads": 32,
+  "num_experts": 0,
+  "num_experts_per_tok": 0,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 8,
+  "num_shared_experts": 0,
+  "original_max_position_embeddings": 8192,
+  "output_router_logits": false,
+  "pad_token_id": 64255,
+  "query_key_norm": false,
+  "rms_norm_eps": 1e-06,
+  "rope_head_dim": 64,
+  "rope_parameters": {
+    "attention_factor": 1.2772588722239782,
+    "beta_fast": 128.0,
+    "beta_slow": 4.0,
+    "factor": 16.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "yarn",
+    "truncate": true
+  },
+  "rope_theta": 1000000.0,
+  "router_aux_loss_coef": 0.001,
+  "router_scaling_factor": null,
+  "router_score_func": "sigmoid",
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.57.1",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 64256
+}