If by lower-end Macbook air, you mean with 8GB of memory, try the smaller models (Such as Orca Mini 3B). You can do this via LM Studio, Oogabooga/text-generation-webui, KoboldCPP, GPT4all, ctransformers, and more.
I'm biased since I work on Ollama, and if you want to try it out:
1. Download https://ollama.ai/download
2. `ollama run orca`
3. Enter your input to prompt
Note Ollama is open source, and you can compile it too from https://github.com/jmorganca/ollama
For now:
You should have at least 8 GB of RAM to run the 3B models, 16 GB to run the 7B models, and 32 GB to run the 13B models.
My personal recommendation is to get as much memory as you can if you want to work with local models [including VRAM if you are planning to be executing on GPU]
As a datapoint, I have a 30B model [0] loaded right now and it's using 23.44GB of RAM. Getting around 9 tokens/sec, which is very usable. I also have the 65B version of the same model [1] and it's good for around 3.6 tokens/second, but it uses 44GB of RAM. Not unusably slow, but more often than not I opt for the 30B because it's good enough and a lot faster.
Haven't tried the llama2 70B yet.
[0] https://huggingface.co/TheBloke/upstage-llama-30b-instruct-2... [1] https://huggingface.co/TheBloke/Upstage-Llama1-65B-Instruct-...