Instructions to use lmsys/vicuna-33b-v1.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lmsys/vicuna-33b-v1.3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="lmsys/vicuna-33b-v1.3")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("lmsys/vicuna-33b-v1.3") model = AutoModelForCausalLM.from_pretrained("lmsys/vicuna-33b-v1.3") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use lmsys/vicuna-33b-v1.3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lmsys/vicuna-33b-v1.3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lmsys/vicuna-33b-v1.3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/lmsys/vicuna-33b-v1.3
- SGLang
How to use lmsys/vicuna-33b-v1.3 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 "lmsys/vicuna-33b-v1.3" \ --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": "lmsys/vicuna-33b-v1.3", "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 "lmsys/vicuna-33b-v1.3" \ --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": "lmsys/vicuna-33b-v1.3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use lmsys/vicuna-33b-v1.3 with Docker Model Runner:
docker model run hf.co/lmsys/vicuna-33b-v1.3
Adding `safetensors` variant of this model
#13 opened about 2 years ago
by
SFconvertbot
Adding Evaluation Results
#11 opened over 2 years ago
by
leaderboard-pr-bot
When we can expect vicuna variant of CodeLlama-2 34b model?
๐ 1
#10 opened over 2 years ago
by
perelmanych
Failed. Reason: The primary container for production variant AllTraffic did not pass the ping health check
#9 opened over 2 years ago
by
Shivam1410
Bigger is NOT always better...
๐ 1
5
#8 opened almost 3 years ago
by
MrDevolver
Adding `safetensors` variant of this model
#6 opened almost 3 years ago
by
mmahlwy3
Adding `safetensors` variant of this model
#5 opened almost 3 years ago
by
mmahlwy3
How much GPU graphics memory is required for deployment
2
#3 opened almost 3 years ago
by
chenfeicqq
Is there a 4bit quantize version for the FastChat?
6
#2 opened almost 3 years ago
by
ruradium
Prompt format?
10
#1 opened almost 3 years ago
by
Thireus