Delete load_model.py

load_model.py

@@ -1,44 +0,0 @@
-from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig
-
-model_link = "SSahas/openai_community_med_e3"
-tokenizer = AutoTokenizer.from_pretrained(model_link)
-finetuned_model = AutoModelForCausalLM.from_pretrained(model_link)
-original_model  = AutoModelForCausalLM.from_pretrained("openai-community/gpt2-medium")
-
-prompt = [{'role': 'user', 'content': 'Hey man , you wanna buy some weed ?'},
- {'role': 'assistant', 'content': 'Some what ?'},
- {'role': 'user',
-  'content': 'Weed ! You know ? Pot , Ganja , Mary Jane some chronic !'},
- {'role': 'assistant', 'content': 'Oh , umm , no thanks .'},
- {'role': 'user',
-  'content': 'I also have blow if you prefer to do a few lines .'},
- {'role': 'assistant', 'content': 'No , I am ok , really .'},
- {'role': 'user',
-  'content': 'Come on man ! I even got dope and acid ! Try some !'},
- {'role': 'assistant',
-  'content': 'Do you really have all of these drugs ? Where do you get them from ?'},
- {'role': 'user',
-  'content': 'I got my connections ! Just tell me what you want and I ’ ll even give you one ounce for free .'},
-   {'role': 'assistant', 'content': 'Sounds good ! Let''s see , I want .'},
- {'role': 'user', 'content': 'Yeah ?'}]
-
-
-prompt = [{'role': 'user', 'content': 'Hello, My name is Sahas., How are you?'},]
-
-
-input_text = tokenizer.apply_chat_template(prompt,tokenize = False, truncation=False, add_generation_prompt=True)
-    #print(input_text)
-input_ids = tokenizer(input_text,padding = True, return_tensors = "pt")
-#print(input_ids)
-#output = model.generate(input_ids=input_ids['input_ids'], generation_config=GenerationConfig(max_new_tokens=25,temperature = 0.1, eos_token_id = 50256, repetition_penalty = 1.9, do_sample= True))
-finetuned_model_output = finetuned_model.generate(input_ids=input_ids['input_ids'], generation_config=GenerationConfig(max_new_tokens=20,pad_token_id = 50256, temperature = 0.5,  do_sample= True))
-#print(output)
-original_model_output = original_model.generate(input_ids=input_ids['input_ids'], generation_config=GenerationConfig(max_new_tokens=20, temperature = 0.5,  do_sample= True))
-finetuned_model_output = tokenizer.decode(finetuned_model_output[0][input_ids['input_ids'].shape[1]:], skip_special_tokens=True)
-original_model_output = tokenizer.decode(original_model_output[0][input_ids['input_ids'].shape[1]:], skip_special_tokens=True)
-
-print("finetuned_model outptut\\n")
-print(finetuned_model_output)
-print("original_model outptut\\n")
-print(original_model_output)
-