Update README.md

README.md

@@ -30,7 +30,6 @@ This project is for research purposes only. Third-party datasets may be subject
 import torch
 from unsloth import FastLanguageModel
 from transformers import AutoTokenizer, pipeline
-model_id='FinLang/investopedia_chat_model'
 max_seq_length=2048
 model, tokenizer = FastLanguageModel.from_pretrained(
         model_name = "anamikac2708/Gemma-7b-finetuned-investopedia-Merged-FP16", # YOUR MODEL YOU USED FOR TRAINING
@@ -38,7 +37,6 @@ model, tokenizer = FastLanguageModel.from_pretrained(
         dtype = torch.bfloat16,
         #load_in_4bit = True,  # IF YOU WANT TO LOAD WITH BITSANDBYTES INT4
     )
-tokenizer = AutoTokenizer.from_pretrained(model_id)
 pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
 example = [{'content': 'You are a financial expert and you can answer any questions related to finance. You will be given a context and a question. Understand the given context and\n        try to answer. Users will ask you questions in English and you will generate answer based on the provided CONTEXT.\n        CONTEXT:\n        D. in Forced Migration from the University of the Witwatersrand (Wits) in Johannesburg, South Africa; A postgraduate diploma in Folklore & Cultural Studies at Indira Gandhi National Open University (IGNOU) in New Delhi, India; A Masters of International Affairs at Columbia University; A BA from Barnard College at Columbia University\n', 'role': 'system'}, {'content': ' In which universities did the individual obtain their academic qualifications?\n', 'role': 'user'}, {'content': ' University of the Witwatersrand (Wits) in Johannesburg, South Africa; Indira Gandhi National Open University (IGNOU) in New Delhi, India; Columbia University; Barnard College at Columbia University.', 'role': 'assistant'}]
 prompt = pipe.tokenizer.apply_chat_template(example[:2], tokenize=False, add_generation_prompt=True)