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
Is this tokenizer messed up?
I've noticed sometimes the model returns \n\nUSER: at the end of some responses however I don't encounter this issue on your 13b-v2 version. Are they different between the models? I'm using vicuna formatting for multi turn.
Thanks to the team for all the work they put into this model btw, it's very impressive.
I have noticed this happening when the prompt templating is not correct. Try checking if the prompts are in the right format.
Ahh that's what it is: I was using USER: ASSISTANT: template for 13b but it looks like 70b is ### User:\nWrite a python flask code for login management\n\n### Assistant:\n, switching to that format fixed it, thank you!
Out of curiosity are the new lines needed? eg. \n after User: Assistant: and after the response? \n\n? This formatting template stuff has been hard for me to understand while experimenting with LLMs.
Thanks again!