Instructions to use recursal/radlads-7b-various with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use recursal/radlads-7b-various with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="recursal/radlads-7b-various")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("recursal/radlads-7b-various", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use recursal/radlads-7b-various with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "recursal/radlads-7b-various" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "recursal/radlads-7b-various", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/recursal/radlads-7b-various
- SGLang
How to use recursal/radlads-7b-various 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 "recursal/radlads-7b-various" \ --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": "recursal/radlads-7b-various", "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 "recursal/radlads-7b-various" \ --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": "recursal/radlads-7b-various", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use recursal/radlads-7b-various with Docker Model Runner:
docker model run hf.co/recursal/radlads-7b-various
[Request] Include Explanations of Checkpoints
#3
by codys12 - opened
A short explanation of which checkpoint corrosponds to wich training stage, dataset, etc. This would be very useful for replication and extenstion of your method!
Thanks for reminding us about this, I've updated the radlads-7b-various README with these descriptions!
SmerkyG changed discussion status to closed