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| 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)`); | |
| }); | |
| }); | |