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optimum-intel library:1from optimum.intel import OVModelForCausalLM
2from transformers import AutoTokenizer
3
4model_id = "CelesteImperia/Phi-3.5-mini-instruct-OpenVINO-INT8"
5tokenizer = AutoTokenizer.from_pretrained(model_id)
6model = OVModelForCausalLM.from_pretrained(model_id)
7
8prompt = "Solve this step-by-step: If 3x + 5 = 20, what is x?"
9inputs = tokenizer(prompt, return_tensors="pt")
10outputs = model.generate(**inputs, max_new_tokens=150)
11print(tokenizer.decode(outputs[0], skip_special_tokens=True))OpenVINO.GenAI NuGet integration, offering an efficient path for embedding high-logic agents into Windows software.1using OpenVino.GenAI;
2
3// 1. Initialize the LLM Pipeline
4var device = "CPU"; // Use "GPU" for RTX acceleration
5using var pipe = new LLMPipeline("path/to/phi-3.5-int8-model", device);
6
7// 2. Set Generation Config
8var config = new GenerationConfig { MaxNewTokens = 300, Temperature = 0.5f };
9
10// 3. Execute Inference
11var prompt = "Explain the difference between an Interface and an Abstract Class in C#.";
12var result = pipe.Generate(prompt, config);
13
14Console.WriteLine(result);| Platform | Support Link |
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