Text Generation
Transformers
Safetensors
English
llama
Merge
conversational
text-generation-inference
Instructions to use alpindale/goliath-120b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alpindale/goliath-120b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="alpindale/goliath-120b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("alpindale/goliath-120b") model = AutoModelForCausalLM.from_pretrained("alpindale/goliath-120b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use alpindale/goliath-120b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "alpindale/goliath-120b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "alpindale/goliath-120b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/alpindale/goliath-120b
- SGLang
How to use alpindale/goliath-120b 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 "alpindale/goliath-120b" \ --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": "alpindale/goliath-120b", "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 "alpindale/goliath-120b" \ --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": "alpindale/goliath-120b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use alpindale/goliath-120b with Docker Model Runner:
docker model run hf.co/alpindale/goliath-120b
Is this really just a merge of two other models?
#13
by tachyphylaxis - opened
The strings of gratuitously alliterative narrative I've coaxed out of this thing are absolutely unparalleled. It utterly trounces anything I've ever written in that respect. Granted, I'm still convalescing from years of COVID isolation brain rot, but--HOW? How did you do this??!?