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adding wwdc25 samples (#1370)

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This commit is contained in:
Shashank
2025-06-10 10:23:25 -07:00
committed by GitHub
parent 977cd30242
commit 4b2a0df237
15 changed files with 6053 additions and 0 deletions
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385
wwdc25/WWDC25MLXSwiftExamples/WWDC25MLXSwiftExamples.xcodeproj/project.pbxproj Normal file
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7
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25
wwdc25/WWDC25MLXSwiftExamples/WWDC25MLXSwiftExamples/SimpleMLXLM.swift Normal file
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import Foundation
import MLX
import MLXLMCommon
import MLXLLM
func SimpleMLXLM() async throws {
// Load the model and tokenizer directly from HF
let modelId = "mlx-community/Mistral-7B-Instruct-v0.3-4bit"
let modelFactory = LLMModelFactory.shared
let configuration = ModelConfiguration(id: modelId)
let model = try await modelFactory.loadContainer(configuration: configuration)
try await model.perform({context in
// Prepare the prompt for the model
let prompt = "Write a quicksort in Swift"
let input = try await context.processor.prepare(input: UserInput(prompt: prompt))
// Generate the text
let params = GenerateParameters(temperature: 0.0)
let tokenStream = try generate(input: input, parameters: params, context: context)
for await part in tokenStream {
print(part.chunk ?? "", terminator: "")
}
})
}

48
wwdc25/WWDC25MLXSwiftExamples/WWDC25MLXSwiftExamples/SimpleMLXLMWithKVCache.swift Normal file
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import Foundation
import MLX
import MLXLMCommon
import MLXLLM
func SimpleMLXLMWithKVCache() async throws {
// Load the model and tokenizer directly from HF
let modelId = "mlx-community/Mistral-7B-Instruct-v0.3-4bit"
let modelFactory = LLMModelFactory.shared
let configuration = ModelConfiguration(id: modelId)
let model = try await modelFactory.loadContainer(configuration: configuration)
try await model.perform({context in
// Prepare the prompt for the model
let prompt = "Write a quicksort in Swift"
let input = try await context.processor.prepare(input: UserInput(prompt: prompt))
// Create the key-value cache
let generateParameters = GenerateParameters()
let cache = context.model.newCache(parameters: generateParameters)
// Low level token iterator
let tokenIter = try TokenIterator(input: input,
model: context.model,
cache: cache,
parameters: generateParameters)
let tokenStream = generate(input: input, context: context, iterator: tokenIter)
for await part in tokenStream {
print(part.chunk ?? "", terminator: "")
}
print("\n=============================================================================\n")
// Prompt the model again with a follow up questions:
let newPrompt = "What is it's time complexity?"
let newInput = try await context.processor.prepare(input: .init(prompt: newPrompt))
let newTokenIter = try TokenIterator(input: newInput,
model: context.model,
cache: cache,
parameters: generateParameters)
let newTokenStream = generate(input: newInput, context: context, iterator: newTokenIter)
for await part in newTokenStream {
print(part.chunk ?? "", terminator: "")
}
})
}

32
wwdc25/WWDC25MLXSwiftExamples/WWDC25MLXSwiftExamples/main.swift Normal file
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// WWDC Session: Get started with MLX for Apple silicon
// Swift
import MLX
// Make an array
let a = MLXArray([1, 2, 3])
// Make another array
let b = MLXArray([1, 2, 3])
// Do an operation
let c = a + b
// Access information about the array
let shape = c.shape
let dtype = c.dtype
// Print results
print("a: \(a)")
print("b: \(b)")
print("c = a + b: \(c)")
print("shape: \(shape)")
print("dtype: \(dtype)")
// WWDC Session: Explore large language models on Apple silicon with MLX
/// Example 1: Simple MLXLM Swift example using Mistral-7B-Instruct-v0.3-4bit
try await SimpleMLXLM()
/// Example 2: Using KVCache and custom TokenIterator with Mistral-7B-Instruct-v0.3-4bit
try await SimpleMLXLMWithKVCache()