Delete app.py

app.py

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-# -*- coding: utf-8 -*-
-"""Inference_LawyerGPT_Finetune_falcon7b_Indian_Law_Data.ipynb
-
-Automatically generated by Colaboratory.
-
-Original file is located at
-    https://colab.research.google.com/drive/1NpBtrGAcXsmoSmM5Sr-INiE5-tU9D37n
-
-### Install requirements
-
-First, run the cells below to install the requirements:
-"""
-
-!nvidia-smi
-
-!pip install -Uqqq pip --progress-bar off
-!pip install -qqq bitsandbytes==0.39.0
-!pip install -qqq torch--2.0.1 --progress-bar off
-!pip install -qqq -U git+https://github.com/huggingface/transformers.git@e03a9cc --progress-bar off
-!pip install -qqq -U git+https://github.com/huggingface/peft.git@42a184f --progress-bar off
-!pip install -qqq -U git+https://github.com/huggingface/accelerate.git@c9fbb71 --progress-bar off
-!pip install -qqq datasets==2.12.0 --progress-bar off
-!pip install -qqq loralib==0.1.1 --progress-bar off
-!pip install einops
-
-import os
-# from pprint import pprint
-# import json
-
-import bitsandbytes as bnb
-import pandas as pd
-import torch
-import torch.nn as nn
-import transformers
-from datasets import load_dataset
-from huggingface_hub import notebook_login
-from peft import (
-    LoraConfig,
-    PeftConfig,
-    get_peft_model,
-    prepare_model_for_kbit_training,
-)
-from transformers import (
-    AutoConfig,
-    AutoModelForCausalLM,
-    AutoTokenizer,
-    BitsAndBytesConfig,
-)
-
-os.environ["CUDA_VISIBLE_DEVICES"] = "0"
-
-notebook_login()
-#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
-
-"""### Load dataset"""
-
-from datasets import load_dataset
-
-dataset_name = "nisaar/Lawyer_GPT_India"
-#dataset_name = "patrick11434/TEST_LLM_DATASET"
-dataset = load_dataset(dataset_name, split="train")
-
-"""## Load adapters from the Hub
-
-You can also directly load adapters from the Hub using the commands below:
-"""
-
-from peft import *
-
-#change peft_model_id
-bnb_config = BitsAndBytesConfig(
-    load_in_4bit=True,
-    load_4bit_use_double_quant=True,
-    bnb_4bit_quant_type="nf4",
-    bnb_4bit_compute_dtype=torch.bfloat16,
-)
-
-peft_model_id = "nisaar/falcon7b-Indian_Law_150Prompts"
-config = PeftConfig.from_pretrained(peft_model_id)
-model = AutoModelForCausalLM.from_pretrained(
-    config.base_model_name_or_path,
-    return_dict=True,
-    quantization_config=bnb_config,
-    device_map="auto",
-    trust_remote_code=True,
-)
-tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
-tokenizer.pad_token = tokenizer.eos_token
-
-
-model = PeftModel.from_pretrained(model, peft_model_id)
-
-"""## Inference
-
-You can then directly use the trained model or the model that you have loaded from the 🤗 Hub for inference as you would do it usually in `transformers`.
-"""
-
-generation_config = model.generation_config
-generation_config.max_new_tokens = 200
-generation_config_temperature = 1
-generation_config.top_p = 0.7
-generation_config.num_return_sequences = 1
-generation_config.pad_token_id = tokenizer.eos_token_id
-generation_config_eod_token_id = tokenizer.eos_token_id
-
-DEVICE = "cuda:0"
-
-# Commented out IPython magic to ensure Python compatibility.
-# %%time
-# prompt = f"""
-# <human>: Who appoints the Chief Justice of India?
-# <assistant>:
-# """.strip()
-# 
-# encoding = tokenizer(prompt, return_tensors="pt").to(DEVICE)
-# with torch.inference_mode():
-#   outputs = model.generate(
-#       input_ids=encoding.attention_mask,
-#       generation_config=generation_config,
-#   )
-# print(tokenizer.decode(outputs[0],skip_special_tokens=True))
-
-def generate_response(question: str) -> str:
-    prompt = f"""
-    <human>: {question}
-    <assistant>:
-    """.strip()
-    encoding = tokenizer(prompt, return_tensors="pt").to(DEVICE)
-    with torch.inference_mode():
-        outputs = model.generate(
-            input_ids=encoding.input_ids,
-            attention_mask=encoding.attention_mask,
-            generation_config=generation_config,
-        )
-    response = tokenizer.decode(outputs[0],skip_special_tokens=True)
-
-    assistant_start = '<assistant>:'
-    response_start = response.find(assistant_start)
-    return response[response_start + len(assistant_start):].strip()
-
-prompt = "Debate the merits and demerits of introducing simultaneous elections in India?"
-print(generate_response(prompt))
-
-prompt = "What are the duties of the President of India as per the Constitution?"
-print(generate_response(prompt))
-
-prompt = "Write a legal memo on the issue of manual scavenging in light of The Prohibition of Employment as Manual Scavengers and their Rehabilitation Act, 2013."
-print(generate_response(prompt))
-
-prompt
-
-prompt = "Explain the concept of 'Separation of Powers' in the Indian Constitution"
-print(generate_response(prompt))
-
-prompt = "Can you explain the steps for registration of a trademark in India?"
-print(generate_response(prompt))
-
-prompt = "What are the potential implications of the proposed Personal Data Protection Bill on tech companies in India?"
-print(generate_response(prompt))
-
-prompt = "Can you draft a non-disclosure agreement (NDA) under Indian law?"
-print(generate_response(prompt))
-
-prompt = "Can you summarize the main points of Article 21 of the Indian Constitution?"
-print(generate_response(prompt))
-
-prompt = "Can you summarize the main arguments of the Supreme Court of India judgment in Kesavananda Bharati v. State of Kerala?"
-print(generate_response(prompt))
-
-prompt = "what is the mysterious case of Advocate Nisaar that was a famous in supreme court of india?"
-print(generate_response(prompt))
-
-prompt = "what is the mysterious case of Advocate Nisaar that was a famous in supreme court of india?"
-print(generate_response(prompt))
-
-prompt = "Can you draft a confidentiality clause for a contract under Indian law?"
-print(generate_response(prompt))
-
-prompt = "How is the concept of 'Economic Justice' enshrined in the Preamble of the Indian Constitution??"
-print(generate_response(prompt))
-
-prompt = "What is the role of the 'Supreme Court' in preserving the fundamental rights of citizens in India?"
-print(generate_response(prompt))
-
-prompt = "Analyze the potential impact of 'Online Education Rights' for students in India?"
-print(generate_response(prompt))
-
-prompt = "Analyze the potential impact of 'Online Education Rights' for students in India?"
-print(generate_response(prompt))
-
-prompt = "Discuss the potential effects of a 'Universal Basic Income' policy in India"
-print(generate_response(prompt))
-
-prompt = "Analyze the potential impact of 'Online Education Rights' for students in India?"
-print(generate_response(prompt))