Instructions to use mbien/recipenlg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbien/recipenlg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mbien/recipenlg")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("mbien/recipenlg") model = AutoModelForCausalLM.from_pretrained("mbien/recipenlg") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use mbien/recipenlg with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mbien/recipenlg" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mbien/recipenlg", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/mbien/recipenlg
- SGLang
How to use mbien/recipenlg 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 "mbien/recipenlg" \ --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": "mbien/recipenlg", "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 "mbien/recipenlg" \ --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": "mbien/recipenlg", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use mbien/recipenlg with Docker Model Runner:
docker model run hf.co/mbien/recipenlg
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Check out the documentation for more information.
RecipeNLG: A Cooking Recipes Dataset for Semi-Structured Text Generation
Model accompanying our INLG 2020 paper: RecipeNLG: A Cooking Recipes Dataset for Semi-Structured Text Generation
Where is the dataset?
Please visit the website of our project: recipenlg.cs.put.poznan.pl to download it.
How to use the model? Could you explain X andy Y?
Yes, sure! If you feel some information is missing in our paper, please check first in our thesis, which is much more detailed. In case of further questions, you're invited to send us a github issue, we will respond as fast as we can!
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docker model run hf.co/mbien/recipenlg