Instructions to use bonadossou/microsoft-elem2design-finetuning-crello-ours with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bonadossou/microsoft-elem2design-finetuning-crello-ours with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "bonadossou/microsoft-elem2design-finetuning-crello-ours") - Transformers
How to use bonadossou/microsoft-elem2design-finetuning-crello-ours with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="bonadossou/microsoft-elem2design-finetuning-crello-ours")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("bonadossou/microsoft-elem2design-finetuning-crello-ours", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use bonadossou/microsoft-elem2design-finetuning-crello-ours with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bonadossou/microsoft-elem2design-finetuning-crello-ours" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bonadossou/microsoft-elem2design-finetuning-crello-ours", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/bonadossou/microsoft-elem2design-finetuning-crello-ours
- SGLang
How to use bonadossou/microsoft-elem2design-finetuning-crello-ours 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 "bonadossou/microsoft-elem2design-finetuning-crello-ours" \ --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": "bonadossou/microsoft-elem2design-finetuning-crello-ours", "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 "bonadossou/microsoft-elem2design-finetuning-crello-ours" \ --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": "bonadossou/microsoft-elem2design-finetuning-crello-ours", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use bonadossou/microsoft-elem2design-finetuning-crello-ours with Docker Model Runner:
docker model run hf.co/bonadossou/microsoft-elem2design-finetuning-crello-ours
- Xet hash:
- c00b08076cb088079d9ad4b80f0eddbec941110fef48c15e90b75508fa4a5729
- Size of remote file:
- 15.4 kB
- SHA256:
- 509160dedf976d719555ed8b6600cd12eb5333839ce4aeeb5bbed8e31d7494f4
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