--- library_name: transformers tags: - OUAF - Oracle - 4GL license: mit language: - en base_model: - microsoft/phi-2 --- ### Model Description Generate 4GL Scripts from english prompts - **Developed by:** Amith Sourya Sadineni - **Model type:** Text Generation - **Language(s):** Python - **License:** MIT - **Finetuned from model:** microsoft/phi-2 ### Model Sources - **Repository:** https://huggingface.co/amithsourya/Script-Generate-4GL-V2.0/blob/main/adapter_model.safetensors - **Demo:** ```python from transformers import AutoModelForCausalLM, AutoTokenizer from peft import PeftModel, PeftConfig lora_path = "amithsourya/Script-Generate-4GL-V2.0" peft_config = PeftConfig.from_pretrained(lora_path) base_model = AutoModelForCausalLM.from_pretrained( peft_config.base_model_name_or_path, device_map="auto", torch_dtype="auto" ) model = PeftModel.from_pretrained(base_model, lora_path) tokenizer = AutoTokenizer.from_pretrained(peft_config.base_model_name_or_path) import re def clean_output(text): return re.sub(r'""([^""]+)""', r'"\1"', text) from transformers import pipeline pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device_map="auto") prompt = "Invoke a Service Script using Save point dispatcher" output = pipe( prompt, max_new_tokens=256, eos_token_id=tokenizer.eos_token_id, return_full_text=False ) print(clean_output(output[0]["generated_text"])) ``` ## Environmental Impact Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** T4 GPU - **Hours used:** 2H:30M ## Example ![image/png](https://cdn-uploads.huggingface.co/production/uploads/682b328fb814376780257a17/JyCAflY-N1QQe0BWeplTa.png) ![image/png](https://cdn-uploads.huggingface.co/production/uploads/682b328fb814376780257a17/kteVhgJZluGYKwg5bxG_m.png)