Prox-Phi-3-mini-128k is a fine-tuned version of Microsoft's Phi-3-mini-128k architecture, tailored for specialized applications in code generation and cybersecurity. This model, with 3.8 billion parameters, provides efficient deployment and robust performance, making it well-suited for tasks such as hacking simulations and vulnerability analysis.
Review and verify outputs carefully, especially for critical applications. Expert validation is recommended to avoid biased or inconsistent content. Use responsibly and ethically, complying with applicable laws and regulations to prevent misuse for malicious purposes.
The model was fine-tuned on a proprietary dataset from OpenVoid, featuring high-quality text data related to coding, cybersecurity, and hacking. Extensive filtering and preprocessing ensured data quality and relevance.
1from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
2
3model_id = "openvoid/Prox-Phi-3-mini-128k"
4
5tokenizer = AutoTokenizer.from_pretrained(model_id)
6model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", trust_remote_code=True)
7
8pipe = pipeline(
9 "text-generation",
10 model=model,
11 tokenizer=tokenizer,
12)
13
14generation_args = {
15 "max_new_tokens": 500,
16 "return_full_text": False,
17 "temperature": 0.0,
18 "do_sample": False,
19}
20
21input_text = "You are a helpful AI assistant. Can you introduce yourself?"
22
23output = pipe(input_text, **generation_args)
24print(output[0]['generated_text'])
