Text Generation
Transformers
PyTorch
English
llama
upstage
llama-2
instruct
instruction
text-generation-inference
Instructions to use upstage/SOLAR-0-70b-16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use upstage/SOLAR-0-70b-16bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="upstage/SOLAR-0-70b-16bit")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("upstage/SOLAR-0-70b-16bit") model = AutoModelForCausalLM.from_pretrained("upstage/SOLAR-0-70b-16bit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use upstage/SOLAR-0-70b-16bit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "upstage/SOLAR-0-70b-16bit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "upstage/SOLAR-0-70b-16bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/upstage/SOLAR-0-70b-16bit
- SGLang
How to use upstage/SOLAR-0-70b-16bit 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 "upstage/SOLAR-0-70b-16bit" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "upstage/SOLAR-0-70b-16bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "upstage/SOLAR-0-70b-16bit" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "upstage/SOLAR-0-70b-16bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use upstage/SOLAR-0-70b-16bit with Docker Model Runner:
docker model run hf.co/upstage/SOLAR-0-70b-16bit
- Xet hash:
- c5857f66317f98fb899fdb61ac3de50c69c2a4e36e5358ea08ec5c2db284bc47
- Size of remote file:
- 9.8 GB
- SHA256:
- f9ff3e0de46264051b08719e124b004c8ce6b2fc396e99f08e3939a2be08e42f
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