modal
Category: data-science-and-ml · License: Apache-2.0 · Version: 1.3
Tags: serverless GPU, cloud computing, model deployment, ML inference
When to use it
Modal is a serverless cloud platform for running Python on demand, including on-demand GPUs. Use when deploying or serving AI/ML models, running GPU-accelerated workloads (training, fine-tuning, inference), serving web endpoints, scheduling batch jobs, or scaling Python code to cloud containers with the Modal SDK.Example requests
Ask your agent in plain language, for example:- “How do I run my PyTorch script on an H100 without owning one?”
- “I’m fine-tuning Llama-3-8B with LoRA using train.py and my checkpoints keep vanishing when the container exits. I need to run it on 4 A100-80GB GPUs on Modal, keep the base weights cached between runs, and pull the HF_TOKEN from a secret. Can you restructure it?”
- “I have 5,000 protein FASTA files and a Python function that scores each one. It takes about 10 minutes per file on my laptop. I’d like it to fan out across lots of cloud machines, then run again automatically every Sunday night with the results collected in one place.”
Install
/plugin marketplace add KalarisLabs/research-agent-skills and install the whole data-science-and-ml category with /plugin install data-science-and-ml@research-agent-skills.