Instructions to use OrionStarAI/Orion-14B-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OrionStarAI/Orion-14B-Chat with Transformers:

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

pipe = pipeline("text-generation", model="OrionStarAI/Orion-14B-Chat", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("OrionStarAI/Orion-14B-Chat", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use OrionStarAI/Orion-14B-Chat with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf OrionStarAI/Orion-14B-Chat
# Run inference directly in the terminal:
llama cli -hf OrionStarAI/Orion-14B-Chat

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf OrionStarAI/Orion-14B-Chat
# Run inference directly in the terminal:
llama cli -hf OrionStarAI/Orion-14B-Chat

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf OrionStarAI/Orion-14B-Chat
# Run inference directly in the terminal:
./llama-cli -hf OrionStarAI/Orion-14B-Chat

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf OrionStarAI/Orion-14B-Chat
# Run inference directly in the terminal:
./build/bin/llama-cli -hf OrionStarAI/Orion-14B-Chat

Use Docker

docker model run hf.co/OrionStarAI/Orion-14B-Chat

LM Studio
Jan

vLLM

How to use OrionStarAI/Orion-14B-Chat with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OrionStarAI/Orion-14B-Chat"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OrionStarAI/Orion-14B-Chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/OrionStarAI/Orion-14B-Chat

SGLang

How to use OrionStarAI/Orion-14B-Chat 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 "OrionStarAI/Orion-14B-Chat" \
    --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": "OrionStarAI/Orion-14B-Chat",
		"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 "OrionStarAI/Orion-14B-Chat" \
        --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": "OrionStarAI/Orion-14B-Chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use OrionStarAI/Orion-14B-Chat with Ollama:
```
ollama run hf.co/OrionStarAI/Orion-14B-Chat
```
Unsloth Desktop
Docker Model Runner
How to use OrionStarAI/Orion-14B-Chat with Docker Model Runner:
```
docker model run hf.co/OrionStarAI/Orion-14B-Chat
```

Lemonade

How to use OrionStarAI/Orion-14B-Chat with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull OrionStarAI/Orion-14B-Chat

Run and chat with the model

lemonade run user.Orion-14B-Chat-{{QUANT_TAG}}

List all available models

lemonade list

Atomic Chat

Orion-14B-Chat

File size: 771 Bytes

f46de21

{
  "architectures": [
    "OrionForCausalLM"
  ],
  "auto_map": {
    "AutoConfig": "configuration_orion.OrionConfig",
    "AutoModelForCausalLM": "modeling_orion.OrionForCausalLM"
  },
  "bos_token_id": 1,
  "eos_token_id": 2,
  "hidden_act": "silu",
  "hidden_size": 5120,
  "model_type": "orion",
  "initializer_range": 0.02,
  "intermediate_size": 15360,
  "max_position_embeddings": 4096,
  "max_sequence_length": 4096,
  "num_attention_heads": 40,
  "num_hidden_layers": 40,
  "num_key_value_heads": 40,
  "pad_token_id": 0,
  "pretraining_tp": 1,
  "rms_norm_eps": 1e-05,
  "rope_scaling": null,
  "rope_theta": 10000.0,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.34.0",
  "use_cache": true,
  "vocab_size": 84608
}