Instructions to use budecosystem/genz-70b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use budecosystem/genz-70b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="budecosystem/genz-70b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("budecosystem/genz-70b") model = AutoModelForCausalLM.from_pretrained("budecosystem/genz-70b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use budecosystem/genz-70b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "budecosystem/genz-70b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "budecosystem/genz-70b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/budecosystem/genz-70b
- SGLang
How to use budecosystem/genz-70b 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 "budecosystem/genz-70b" \ --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": "budecosystem/genz-70b", "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 "budecosystem/genz-70b" \ --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": "budecosystem/genz-70b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use budecosystem/genz-70b with Docker Model Runner:
docker model run hf.co/budecosystem/genz-70b
Dataset details
Do you plan on releasing the exact dataset used to train GenZ, or at least a complete list of all data sources used in finetuning?
Currently, we are not planning to release the dataset. We are currently working on a new model and we would probably release the data along with it.
I note that you didn't answer the second part of the question yet: how about "or at least a complete list of all data sources used in finetuning"? Even if you cannot / will not release the data, knowing exactly what went into it is key for better understanding and evaluating the model. It's the kind of thing one would expect for an initiative with a stated aim of "Democratizing access to LLMs for the open-source community."
Thank you for your time!