| import { describe, expect, it } from "vitest"; |
| import type { ModelData } from "./model-data.js"; |
| import { llama_cpp_python } from "./model-libraries-snippets.js"; |
|
|
| describe("model-libraries-snippets", () => { |
| it("llama_cpp_python conversational", async () => { |
| const model: ModelData = { |
| id: "bartowski/Llama-3.2-3B-Instruct-GGUF", |
| pipeline_tag: "text-generation", |
| tags: ["conversational"], |
| inference: "", |
| }; |
| const snippet = llama_cpp_python(model); |
|
|
| expect(snippet.join("\n")).toEqual(`# !pip install llama-cpp-python |
| |
| from llama_cpp import Llama |
| |
| llm = Llama.from_pretrained( |
| repo_id="bartowski/Llama-3.2-3B-Instruct-GGUF", |
| filename="{{GGUF_FILE}}", |
| ) |
| |
| llm.create_chat_completion( |
| messages = [ |
| { |
| "role": "user", |
| "content": "What is the capital of France?" |
| } |
| ] |
| )`); |
| }); |
|
|
| it("llama_cpp_python non-conversational", async () => { |
| const model: ModelData = { |
| id: "mlabonne/gemma-2b-GGUF", |
| tags: [""], |
| inference: "", |
| }; |
| const snippet = llama_cpp_python(model); |
|
|
| expect(snippet.join("\n")).toEqual(`# !pip install llama-cpp-python |
| |
| from llama_cpp import Llama |
| |
| llm = Llama.from_pretrained( |
| repo_id="mlabonne/gemma-2b-GGUF", |
| filename="{{GGUF_FILE}}", |
| ) |
| |
| output = llm( |
| "Once upon a time,", |
| max_tokens=512, |
| echo=True |
| ) |
| print(output)`); |
| }); |
| }); |
|
|