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transformers library from Hugging Face.pip install transformers1import torch
2from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
3
4torch.random.manual_seed(0)
5
6model = AutoModelForCausalLM.from_pretrained(
7 "Syed-Hasan-8503/Phi-3-mini-4K-instruct-cpo-simpo",
8 device_map="cuda",
9 torch_dtype="auto",
10 trust_remote_code=True,
11)
12tokenizer = AutoTokenizer.from_pretrained("Syed-Hasan-8503/Phi-3-mini-4K-instruct-cpo-simpo")
13
14messages = [
15 {"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"},
16 {"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."},
17 {"role": "user", "content": "What about solving an 2x + 3 = 7 equation?"},
18]
19
20pipe = pipeline(
21 "text-generation",
22 model=model,
23 tokenizer=tokenizer,
24)
25
26generation_args = {
27 "max_new_tokens": 500,
28 "return_full_text": False,
29 "temperature": 0.0,
30 "do_sample": False,
31}
32
33output = pipe(messages, **generation_args)
34print(output[0]['generated_text'])