alpaca-lora/generate.py
2023-03-14 15:10:33 -07:00

41 lines
1.0 KiB
Python

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, "tloen/alpaca-lora-7b")
PROMPT = """Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
Tell me something about alpacas.
### 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))