Help with Llama 2 Finetuning Setup

Beginners
1

Hello!
I’m trying to follow the Llama 2 finetunning example provided by databricks here https://github.com/databricks/databricks-ml-examples/blob/b1ca47c058461f7fde214914d53b051990064d94/llm-models/llamav2/llamav2-7b/scripts/fine_tune_deepspeed.py#L94 . However, I ran into the following issue “lib/python3.9/site-packages/transformers/generation/configuration_utils.py”, line 354, in validate
raise ValueError(
ValueError: do_sample is set to False. However, temperature is set to 0.9 – this flag is only used in sample-based generation modes. Set do_sample=True or unset temperature to continue." on the " model = transformers.AutoModelForCausalLM.from_pretrained(
pretrained_model_name_or_path,
torch_dtype=torch.float16,
trust_remote_code=True,
use_auth_token=True,
)" line for the meta-llama/Llama-2-7b-chat-hf model. I don’t set temperature anywhere in the script.
Does anyone have any idea what the issue is?

3 Likes
2

try setting the temperature parameter to 0.1 while initialising the hugging face pipeline

3

ValueError: do_sample is set to False. However, temperature is set to 0.9 – this flag is only used in sample-based generation modes. Set do_sample=True or unset temperature to continue.

my code is:

from transformers import GenerationConfig, LlamaForCausalLM, LlamaTokenizer

MODEL_NAME = “meta-llama/Llama-2-7b-chat-hf”

bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_use_double_quant=True,
bnb_4bit_quant_type=“nf4”,
bnb_4bit_compute_dtype=torch.bfloat16,
)

model = LlamaForCausalLM.from_pretrained(
MODEL_NAME,
device_map=“auto”,
trust_remote_code=True,
use_auth_token=True,
temperature=0.1,
do_sample=True,
quantization_config=bnb_config,
)

tokenizer = LlamaTokenizer.from_pretrained(MODEL_NAME)
tokenizer.pad_token = tokenizer.eos_token

i explicitly change the do_sample=True in configuration_utils.py but didn`t worked

2 Likes
4

I am having the same issue. It was working without problem until last night.
I tried to change the config file and update it by adding do_sample=true but did not work.

!pip install -qqq bitsandbytes --progress-bar off

!pip install -qqq torch --progress-bar off

!pip install -q -U git+https://github.com/huggingface/transformers.git

MODEL_NAME = “meta-llama/Llama-2-7b-chat-hf”

model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, device_map=“auto”, quantization_config=bnb_config)

Error msg:

ValueError Traceback (most recent call last)
in <cell line: 1>()
----> 1 model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, device_map=“auto”, quantization_config=bnb_config)

5 frames
/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py in validate(self)
352 )
353 if self.temperature != 1.0:
→ 354 raise ValueError(
355 greedy_wrong_parameter_msg.format(flag_name=“temperature”, flag_value=self.temperature)
356 )

ValueError: do_sample is set to False. However, temperature is set to 0.9 – this flag is only used in sample-based generation modes. Set do_sample=True or unset temperature to continue.

5

For anyone looking for a solution, it was an issue with the latest release of hugging face transformers released recently. Please downgrade to the previous version !pip install git+https://github.com/huggingface/transformers@v4.31-release to fix the issue.

4 Likes
6

Thank you.

Downgrading made it work :+1:

7

Thanks It works

8

I was using autotrain and got the same error but downgrading transformers didn’t solve the issue.

!pip install huggingface_hub autotrain-advanced
!pip install git+https://github.com/huggingface/transformers@v4.31-release

This is how I installed the package,
Any solution for this

9

besides downgrade any other solution?

10

As the error raised on

File "/usr/local/lib/python3.10/dist-packages/transformers/generation/configuration_utils.py", line 560, in save_pretrained
    raise ValueError(
ValueError: The generation config instance is invalid -- `.validate()` throws warnings and/or exceptions. Fix these issues to save the configuration.

I just comment the code that raised the exception.

11

I’m hitting the same error, doesn’t :hugs: do regression testing? This is code is so brittle, I just tried with release version 4.38.0.dev0 and it still is crapping out.

12

Downgrading to 4.31 did not solve the issue. Can anyone point me to the fix?

13

This solution works. Thank you so much!!

14

I am at version 4.37.2 and I still see the issue. Can anyone let me know, please, if the issue also appears in most recent releases?
Is there any fix on its way?
I tried all suggestions I could find on this issue, none of them worked.

Thanks

15

The latest transformers version I could get actually working & saving was 4.36.2 (it still shows the warning but doesn’t crash). Downgrading more than that caused error with other things (like not knowing what “mistral” is a model for example).

16

version 4.39.2 crashes due to this error.
anybody encounters this ?