File size: 1,644 Bytes
e116e32
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
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