autotrain-advanced

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Prerequisites

• [X] I have read the documentation.
• [X] I have checked other issues for similar problems.

Backend

Local

Interface Used

UI

CLI Command

No response

UI Screenshots & Parameters

No response

Error Logs

ImportError: Using bitsandbytes 8-bit quantization requires Accelerate: pip install accelerate and the latest version of bitsandbytes: pip install -i https://pypi.org/simple/ bitsandbytes

❌ ERROR | 2024-02-26 10:11:57 | autotrain.trainers.common:wrapper:92 - Using bitsandbytes 8-bit quantization requires Accelerate: pip install accelerate and the latest version of bitsandbytes: pip install -i https://pypi.org/simple/ bitsandbytes 🚀 INFO | 2024-02-26 10:11:57 | autotrain.trainers.common:pause_space:49 - Pausing space...

Additional Information

No response

please paste params used and model

Hi @abhishekkrthakur , these are the details:

Task = LLM SFT Model = mistralai/Mixtral-8x7B-Instruct-v0.1

{
  "block_size": 1024,
  "model_max_length": 2048,
  "padding": "right",
  "use_flash_attention_2": false,
  "disable_gradient_checkpointing": false,
  "logging_steps": -1,
  "evaluation_strategy": "epoch",
  "save_total_limit": 1,
  "save_strategy": "epoch",
  "auto_find_batch_size": false,
  "mixed_precision": "fp16",
  "lr": 0.00003,
  "epochs": 3,
  "batch_size": 2,
  "warmup_ratio": 0.1,
  "gradient_accumulation": 1,
  "optimizer": "adamw_torch",
  "scheduler": "linear",
  "weight_decay": 0,
  "max_grad_norm": 1,
  "seed": 42,
  "chat_template": "none",
  "quantization": "int4",
  "target_modules": "all-linear",
  "merge_adapter": false,
  "peft": true,
  "lora_r": 16,
  "lora_alpha": 32,
  "lora_dropout": 0.05
}

are you running it on windows? could you please tell me how you installed autotrain?

I'm running it on Autotrain UI in HuggingFace spaces @abhishekkrthakur (I chose Autotrain's docker template when building the HF space)

same error, it's running on Autotrain UI, i removed "mixed_precision": "fp16" as the space running on CPU using google/gemma model

parameters:

{
  "block_size": 1024,
  "model_max_length": 2048,
  "padding": "right",
  "use_flash_attention_2": false,
  "disable_gradient_checkpointing": false,
  "logging_steps": -1,
  "evaluation_strategy": "epoch",
  "save_total_limit": 1,
  "save_strategy": "epoch",
  "auto_find_batch_size": false,
  "lr": 0.00003,
  "epochs": 3,
  "batch_size": 2,
  "warmup_ratio": 0.1,
  "gradient_accumulation": 1,
  "optimizer": "adamw_torch",
  "scheduler": "linear",
  "weight_decay": 0,
  "max_grad_norm": 1,
  "seed": 42,
  "chat_template": "none",
  "quantization": "int4",
  "target_modules": "all-linear",
  "merge_adapter": false,
  "peft": true,
  "lora_r": 16,
  "lora_alpha": 32,
  "lora_dropout": 0.05
}

you should not remove any params. if you dont want mixed precision, set it to none:

mixed_precision: "none"

Still same error

taking a look!

hello?

have you tried after that? some packages were updated this week. please factory rebuild your autotrain space before trying it.

have you tried after that? some packages were updated this week. please factory rebuild your autotrain space before trying it.

Still getting the error as of current.

Still same.

I'm using google/gemma-7b, will you try it.

Training Data: (data.csv)

text
"human: hello \n bot: id-chat hi nice to meet you"
"human: how are you \n bot: id-chat I am fine"
"human: generate an image of a cat \n bot: id-image a cute furry cat"

Column mapping:-

{"text": "text"}

I get this same dependency issue please provide a fix OR | 2024-03-04 11:17:08 | autotrain.trainers.common:wrapper:91 - train has failed due to an exception: Traceback (most recent call last): File "/app/env/lib/python3.10/site-packages/autotrain/trainers/common.py", line 88, in wrapper return func(args, kwargs) File "/app/env/lib/python3.10/site-packages/autotrain/trainers/clm/main.py", line 230, in train model = AutoModelForCausalLM.from_pretrained( File "/app/env/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py", line 561, in from_pretrained return model_class.from_pretrained( File "/app/env/lib/python3.10/site-packages/transformers/modeling_utils.py", line 3024, in from_pretrained hf_******.validate_environment( File "/app/env/lib/python3.10/site-packages/transformers/quantizers/quantizer_bnb_4bit.py", line 62, in validate_environment raise ImportError( ImportError: Using bitsandbytes 8-bit quantization requires Accelerate: pip install accelerate and the latest version of bitsandbytes: pip install -i https://pypi.org/simple/ bitsandbytes

❌ ERROR | 2024-03-04 11:17:08 | autotrain.trainers.common:wrapper:92 - Using bitsandbytes 8-bit quantization requires Accelerate: pip install accelerate and the latest version of bitsandbytes: pip install -i https://pypi.org/simple/ bitsandbytes 🚀 INFO | 2024-03-04 11:17:08 | autotrain.trainers.common:pause_space:49 - Pausing space...

@abhishekkrthakur I am receiving the same error when running it on google colab:

@SyntaxPratyush Same here, @abhishekkrthakur can you please look into the same..

I also encountered the same issue

Someone says we need to downgrade transformers library to version 4.30, on order to fix this error

However, GemmerTokenizer need to upgrade transformers to version 4.38 ... !!

taking a look again.

I spun up a new autotrain space, added a10g gpu and i am able to train mistralai/Mistral-7B-v0.1 successfully. do you have this issue with a specific gpu or a specific model?

@abhishekkrthakur Could you please show me a detailed tutorial on how to do it on autotrain-advanced as there are no proper explanations on how to do it, I am having specific issues on finding the proper format for train.csv & the column mapping as write know I am getting Error-500: Check Logs for more Info, and the logs are empty

@SyntaxPratyush here is a train.csv for llm task that you can try with: https://github.com/huggingface/autotrain-example-datasets/blob/main/alpaca1k.csv

@abhishekkrthakur column mapping pls

you dont need to change anything in column mapping if you use that file. also, lets not hijack this thread as its a completely different issue. you can post your queries in huggingface forums and i can help there.

ok thanks

while running

which gpu did you use?

i have a local Radeon Pro 575 and chose the free cpu at the beginning

you cannot use peft and quantization on cpu. please select appropriate gpu. e.g. A10g

im closing this issue as its deviating a lot from the title and the originally reported issue doesnt exist. the error appears because users are trying to train gpu models on a cpu machine.