For a modern LLM generator in Lisp, use (easy) or cl-llama + llama.cpp (more powerful). Avoid implementing transformers from scratch unless educational.
Place these in ~/lisp-models/ and point your Lisp code there. ;; Step 1 – install SBCL and Quicklisp ;; Step 2 – in REPL (ql:quickload :cl-gpt2) ;; Step 3 – load model (downloads weights automatically) (defparameter ai (cl-gpt2:load-model :gpt2-medium))
| Model Source | Command / Link | |--------------|----------------| | | wget https://huggingface.co/gpt2/resolve/main/model.safetensors | | BERT | wget https://huggingface.co/bert-base-uncased/resolve/main/pytorch_model.bin | | CodeLlama (7B) | Request from Meta, then download .gguf from Hugging Face |
# Outside Lisp, using wget wget https://huggingface.co/gpt2/resolve/main/pytorch_model.bin Then convert to Lisp-native format using provided scripts. A lightweight Markov chain generator (no neural nets, purely statistical).