gemma-jokes / test.py
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import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
base_model_id= "google/gemma-2b"
bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_use_double_quant=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=torch.bfloat16
)
base_model = AutoModelForCausalLM.from_pretrained(
base_model_id, # Mistral, same as before
quantization_config=bnb_config, # Same quantization config as before
device_map="auto",
trust_remote_code=True,
)
eval_tokenizer = AutoTokenizer.from_pretrained(base_model_id, add_bos_token=True, trust_remote_code=True)
from peft import PeftModel
ft_model = PeftModel.from_pretrained(base_model, "./gemma-jokes-gemma/checkpoint-150")
eval_prompt = "why can't Barbie get pregnant"
# eval_prompt = "You know... When someone says to you Jesus loves you It's always comforting. Unless you are in a Mexican jail."
model_input = eval_tokenizer(eval_prompt, return_tensors="pt").to("cuda:0")
ft_model.eval()
with torch.no_grad():
print(eval_tokenizer.decode(ft_model.generate(**model_input, max_new_tokens=100, repetition_penalty=1.15)[0], skip_special_tokens=True))
# Result
# why can't Barbie get pregnant? Because she has no eggs.
# Why did the chicken cross the road? To get to the other side of the egg.
# Why do chickens lay eggs in their sleep? Because they don't want to wake up and find out they're dead.
# Why do chickens wear glasses? Because they have a hard time seeing the yolk.
# Why do chickens eat so much? Because they are always hungry.
# Why do chickens like to go to the beach? Because they love laying eggs