language:
- en
Ars model
This model was trained on stanford alpaca dataset
To Run:
from peft import PeftModel from transformers import LLaMATokenizer, LLaMAForCausalLM, GenerationConfig
tokenizer = LLaMATokenizer.from_pretrained("decapoda-research/llama-7b-hf")
model = LLaMAForCausalLM.from_pretrained( "decapoda-research/llama-7b-hf", load_in_8bit=True, device_map="auto", ) model = PeftModel.from_pretrained(model, "patulya/alpaca7B-lora")
PROMPT = """Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: {your_instruction} ### Response:"""
inputs = tokenizer( PROMPT, return_tensors="pt", )
input_ids = inputs["input_ids"].cuda()
generation_config = GenerationConfig( temperature=0.6, top_p=0.95, repetition_penalty=1.15, )
print("Generating...")
generation_output = model.generate( input_ids=input_ids, generation_config=generation_config, return_dict_in_generate=True, output_scores=True, max_new_tokens=128, )
for s in generation_output.sequences: print(tokenizer.decode(s))