Instructions to use Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B") model = AutoModelForCausalLM.from_pretrained("Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B 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 Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B # Run inference directly in the terminal: llama cli -hf Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B # Run inference directly in the terminal: llama cli -hf Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B
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 Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B # Run inference directly in the terminal: ./llama-cli -hf Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B
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 Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B # Run inference directly in the terminal: ./build/bin/llama-cli -hf Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B
Use Docker
docker model run hf.co/Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B
- LM Studio
- Jan
- vLLM
How to use Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B
- SGLang
How to use Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B 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 "Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B" \ --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": "Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B", "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 "Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B" \ --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": "Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B with Ollama:
ollama run hf.co/Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B
- Unsloth Desktop
- Docker Model Runner
How to use Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B with Docker Model Runner:
docker model run hf.co/Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B
- Lemonade
How to use Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Saxo/Linkbricks-Horizon-AI-Korean-Advanced-70B
Run and chat with the model
lemonade run user.Linkbricks-Horizon-AI-Korean-Advanced-70B-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
| { | |
| "_name_or_path": "NousResearch/Hermes-3-Llama-3.1-70B", | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 128000, | |
| "eos_token_id": 128039, | |
| "hidden_act": "silu", | |
| "hidden_size": 8192, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 28672, | |
| "max_position_embeddings": 131072, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 64, | |
| "num_hidden_layers": 80, | |
| "num_key_value_heads": 8, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": { | |
| "factor": 8.0, | |
| "high_freq_factor": 4.0, | |
| "low_freq_factor": 1.0, | |
| "original_max_position_embeddings": 8192, | |
| "rope_type": "llama3" | |
| }, | |
| "rope_theta": 500000.0, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.43.2", | |
| "use_cache": true, | |
| "vocab_size": 128256 | |
| } | |