superdrew100/mistral_7b_quotation_attribution

how to use model with gpt4all

import pandas as pd from datasets import load_dataset import re csv_file = "/Users/admin/Downloads/GPT4_output_GPT-2_training_df.csv"

Load the dataset

dataset = load_dataset("csv", data_files=csv_file, split="train")

def stop_on_token_callback(token_id, token_string): # one sentence is enough: if '' in token_string: return False else: return True

alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.

Instruction:

Find out which character said this specific quote along with their gender

Input:

{}

Response:

{}""" num_examples=10 from gpt4all import GPT4All model = GPT4All('/Users/admin/Downloads/model-unsloth.Q4_K_M.gguf') system_template = '''Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.'''

many models use triple hash '###' for keywords, Vicunas are simpler:

prompt_template = """### Instruction: Find out which character said this specific quote along with their gender

Input:

{0}

Response:

""" with model.chat_session(system_template, prompt_template): for i in range(min(num_examples, len(dataset))): row = dataset[i] #response1 = model.generate(row['formatted_input'], callback=stop_on_token_callback) print(i) response1 = model.generate(row['formatted_input']) print(response1) print() print(f"Correct output: {row['TrueSpeaker']}")