Instructions to use LoupGarou/WizardCoder-Guanaco-15B-V1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LoupGarou/WizardCoder-Guanaco-15B-V1.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="LoupGarou/WizardCoder-Guanaco-15B-V1.0")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("LoupGarou/WizardCoder-Guanaco-15B-V1.0") model = AutoModelForCausalLM.from_pretrained("LoupGarou/WizardCoder-Guanaco-15B-V1.0") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use LoupGarou/WizardCoder-Guanaco-15B-V1.0 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LoupGarou/WizardCoder-Guanaco-15B-V1.0" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LoupGarou/WizardCoder-Guanaco-15B-V1.0", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/LoupGarou/WizardCoder-Guanaco-15B-V1.0
- SGLang
How to use LoupGarou/WizardCoder-Guanaco-15B-V1.0 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 "LoupGarou/WizardCoder-Guanaco-15B-V1.0" \ --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": "LoupGarou/WizardCoder-Guanaco-15B-V1.0", "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 "LoupGarou/WizardCoder-Guanaco-15B-V1.0" \ --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": "LoupGarou/WizardCoder-Guanaco-15B-V1.0", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use LoupGarou/WizardCoder-Guanaco-15B-V1.0 with Docker Model Runner:
docker model run hf.co/LoupGarou/WizardCoder-Guanaco-15B-V1.0
What is this model?
Why is this called wizardcoder-guanaco? How is this diffrence from normal wizarcoder?
Model card has been updated to reflect QLORA was used to fine tune WizardCoder 15B on the openassistant-guanaco dataset after it was trimmed down to English only and 2 standard deviations of input-output pair token size.
Wow this model sounds amazing!!! I need to tell the bloke about this so he can quantize it
Yeah looks very interesting.
Am I correct that the prompt template is Alpaca, like WizardCoder?
Im not 100% sure but ive been running it with that preset on oobagooba and its responding correctly