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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/ars")

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))