Days failing to do a basic test with AutoTrain, please help
Hi all,First of all, thank you very much for taking your time to read and answer my question.I’m new in NLP, I just heard about HuggingFace a couple of weeks ago.Since then, I was struggling from morning to night to execute a simple test to see how Auto Train (and Autotrain advanced) work.I’m writing this after literally breaking my head with different attempts and I have a question:Is it possible the reason I didn’t manage to execute the LLM fine tuning task is that I didn’t add a payment method?When I try to use AutoTrain, after selecting a dummy csv with text and target, with 2 columns and 4 rows (Just for testing purposes), it stops the process and automatically selects the 5 candidates mode, requesting a payment method to continue (First time usage, only 4 rows and 2 columns to see what Hugging Face AutoTrain is and how it  works).When I try to use AutoTrain Advanced for LLM Fine tuning, I always get errors. I tried different LLM and different datasets.The process starts and then stops, sometimes without returning the cause of the error, and sometimes the error is ““requests.exceptions.HTTPError: 400 Client Error: Bad Request for url:https://api.autotrain.huggingface.co/projects/X/start_training””.I must mention that since I only want to test and get familiar to H“uggingFace, my estimated costs are always: “Estimated cost: $0.00. Note: clicking on ‘Create Project’ will start training and incur charges!”So my question is, do I need to add a payment method to test Auto Train and otherwise I’m wasting my time thinking the trial is for free, or do you think i’m doing something technically wrong?Thank you.Attach image of the screen I keep getting independently of the task size:image_2023-07-06_0012020831610×870 62.4 KB
2023-07-28T09:05:07Z
Hi, I am getting the same error and assuming the same explanation : I have no payment method yet configured although I am intending to do itAny clue out there ?
2023-08-09T08:51:55Z
Hi, I find myself in the same situation where I’ve been struggling with the same issue for the past three days…Here is a screenshot of my space with the proper settings to train the model and the loaded dataset:image1890×759 51.8 KBAnd here are the logs I receive once I create the project:INFO    task_type: LLM FinetuningINFO    model_choice: HuggingFace HubINFO    Updating hub model choices for task: lm_training, model_choice: HuggingFace HubTraceback (most recent call last):File “/app/env/lib/python3.9/site-packages/gradio/routes.py”, line 442, in run_predictoutput = await app.get_blocks().process_api(File “/app/env/lib/python3.9/site-packages/gradio/blocks.py”, line 1392, in process_apiresult = await self.call_function(File “/app/env/lib/python3.9/site-packages/gradio/blocks.py”, line 1097, in call_functionprediction = await anyio.to_thread.run_sync(File “/app/env/lib/python3.9/site-packages/anyio/to_thread.py”, line 33, in run_syncreturn await get_asynclib().run_sync_in_worker_thread(File “/app/env/lib/python3.9/site-packages/anyio/_backends/_asyncio.py”, line 877, in run_sync_in_worker_threadreturn await futureFile “/app/env/lib/python3.9/site-packages/anyio/_backends/_asyncio.py”, line 807, in runresult = context.run(func, *args)File “/app/env/lib/python3.9/site-packages/gradio/utils.py”, line 703, in wrapperresponse = f(*args, **kwargs)File “/app/src/autotrain/app.py”, line 170, in _update_col_mapdata_cols = pd.read_csv(training_data[0].name, nrows=2).columns.tolist()TypeError: ‘NoneType’ object is not subscriptableINFO    Estimating costs…INFO    model_choice: HuggingFace HubINFO    Updating hub model choices for task: lm_training, model_choice: HuggingFace HubINFO    Estimating costs…INFO    Estimating costs…INFO    Estimating costs…INFO    Estimating number of samplesINFO    Estimating costs for: num_models: 3, task: lm_training, num_samples: 3996INFO    Getting project cost…INFO    Sending GET request tohttps://api.autotrain.huggingface.co/pricing/compute?username=JordanLaforet&task_id=9&num_samples=3996&num_models=3INFO    Estimated_cost: 0INFOCreating project: h1fq-m1lc-mxulINFOTask: lm_trainingINFOTraining data: [<tempfile._TemporaryFileWrapper object at 0x7f6e8e13c850>]INFOValidation data: NoneINFOTraining params: [{“hub_model”: “meta-llama/Llama-2-7b-hf”, “num_models”: 3}]INFOHub model: meta-llama/Llama-2-7b-hfINFOEstimated cost: 0.0INFO:Can pay: FalseINFO    Dataset: h1fq-m1lc-mxul (lm_training)Train data: [‘/tmp/gradio/552a0fe9ac975ff47df0e51f77a96d2ef40f8e6a/Dataset.csv’]Valid data:Column mapping: {‘text’: ‘training_data’}Pushing dataset shards to the dataset hub:   0%|          | 0/1 [00:00<?, ?it/s]Creating parquet from Arrow format:   0%|          | 0/4 [00:00<?, ?ba/s]Creating parquet from Arrow format: 100%|██████████| 4/4 [00:00<00:00, 656.93ba/s]Pushing dataset shards to the dataset hub: 100%|██████████| 1/1 [00:00<00:00,  2.97it/s]Pushing dataset shards to the dataset hub: 100%|██████████| 1/1 [00:00<00:00,  2.97it/s]Pushing dataset shards to the dataset hub:   0%|          | 0/1 [00:00<?, ?it/s]Creating parquet from Arrow format:   0%|          | 0/1 [00:00<?, ?ba/s]Creating parquet from Arrow format: 100%|██████████| 1/1 [00:00<00:00, 712.95ba/s]Pushing dataset shards to the dataset hub: 100%|██████████| 1/1 [00:00<00:00,  5.17it/s]Pushing dataset shards to the dataset hub: 100%|██████████| 1/1 [00:00<00:00,  5.17it/s]Downloading metadata:   0%|          | 0.00/466 [00:00<?, ?B/s]Downloading metadata: 100%|██████████| 466/466 [00:00<00:00, 7.73MB/s]INFOCreating project h1fq-m1lc-mxul, task: lm_trainingINFOUsing username: JordanLaforetINFOUsing param_choice: autotrainINFOUsing hub_model: meta-llama/Llama-2-7b-hfINFOUsing job_params: [{‘hub_model’: ‘meta-llama/Llama-2-7b-hf’, ‘num_models’: 3, ‘task’: ‘lm_training’}]INFOCreating project h1fq-m1lc-mxul, task: lm_trainingINFOCreatin​:rocket:g project with payload: {‘username’: ‘JordanLaforet’, ‘proj_name’: ‘h1fq-m1lc-mxul’, ‘task’: 9, ‘config’: {‘advanced’: True, ‘autotrain’: True, ‘language’: ‘unk’, ‘max_models’: 3, ‘hub_model’: ‘meta-llama/Llama-2-7b-hf’, ‘params’: [{‘hub_model’: ‘meta-llama/Llama-2-7b-hf’, ‘task’: ‘lm_training’}]}}INFO     Creating project with payload: {‘username’: ‘JordanLaforet’, ‘proj_name’: ‘h1fq-m1lc-mxul’, ‘task’: 9, ‘config’: {‘advanced’: True, ‘autotrain’: True, ‘language’: ‘unk’, ‘max_models’: 3, ‘hub_model’: ‘meta-llama/Llama-2-7b-hf’, ‘params’: [{‘hub_model’: ‘meta-llama/Llama-2-7b-hf’, ‘task’: ‘lm_training’}]}}INFO    Sending POST request tohttps://api.autotrain.huggingface.co/projects/createINFO    Sending POST request tohttps://api.autotrain.huggingface.co/projects/81027/data/start_processingINFOWaiting for data processing to complete …INFO    Sending GET request tohttps://api.autotrain.huggingface.co/projects/81027INFO    Sending GET request tohttps://api.autotrain.huggingface.co/projects/81027INFOData processing complete!INFOApproving project # 81027INFO    Sending POST request tohttps://api.autotrain.huggingface.co/projects/81027/start_trainingTraceback (most recent call last):File “/app/env/lib/python3.9/site-packages/gradio/routes.py”, line 442, in run_predictoutput = await app.get_blocks().process_api(File “/app/env/lib/python3.9/site-packages/gradio/blocks.py”, line 1392, in process_apiresult = await self.call_function(File “/app/env/lib/python3.9/site-packages/gradio/blocks.py”, line 1097, in call_functionprediction = await anyio.to_thread.run_sync(File “/app/env/lib/python3.9/site-packages/anyio/to_thread.py”, line 33, in run_syncreturn await get_asynclib().run_sync_in_worker_thread(File “/app/env/lib/python3.9/site-packages/anyio/_backends/_asyncio.py”, line 877, in run_sync_in_worker_threadreturn await futureFile “/app/env/lib/python3.9/site-packages/anyio/_backends/_asyncio.py”, line 807, in runresult = context.run(func, *args)File “/app/env/lib/python3.9/site-packages/gradio/utils.py”, line 703, in wrapperresponse = f(*args, **kwargs)File “/app/src/autotrain/app.py”, line 503, in _create_projectproject.approve(project_id)File “/app/src/autotrain/project.py”, line 201, in approve_ = http_post(File “/app/src/autotrain/utils.py”, line 94, in http_postresponse.raise_for_status()File “/app/env/lib/python3.9/site-packages/requests/models.py”, line 1021, in raise_for_statusraise HTTPError(http_error_msg, response=self)requests.exceptions.HTTPError: 400 Client Error: Bad Request for url:https://api.autotrain.huggingface.co/projects/81027/start_trainingIt appears that the ‘/start_processing’ step runs fine, but the ‘/start_training’ step encounters an issue when making a request to the API. As I’m relatively new to Hugging Face, I’m unsure about the nature of the problem. Any assistance you could provide would be greatly appreciated!
2023-08-10T13:46:33Z
Has anyone ever fixed this? Have this very same issue trying to finetune llama-2-7b-chat-hf using autotrain advanced locally (as of august 10, 2023) and I could not find anything else online.
2023-08-11T10:44:17Z
Yes, take a look at my answer in this topic :Help with autotrain/LLM finetuning pleaseBeginnersThanks for your reply. I checked the logs and the error is: 
File “/app/env/lib/python3.9/site-packages/requests/models.py”, line 1021, in raise_for_status raise HTTPError(http_error_msg, response=self) requests.exceptions.HTTPError: 400 Client Error: Bad Request for url:https://api.autotrain.huggingface.co/projects/80921/start_trainingSo, that doesn’t seem to be an issue with the input data or the configuration of the job. I have not set up a payment method but the job cost estimate was $0.0…Cheers,
2023-08-27T19:47:59Z
I’m not seeing any answers that will help me here.  I’m having the exact same problem as OP, I cannot select to use the free tier, it auto-selects the highest paid tier and demands payment
2023-08-28T09:08:57Z
Short answer : Add a payment method.You are welcome.
2023-09-01T02:29:10Z
Short answer: no. If there’s a free method it should be free. If not, don’t advertise a free method.
2023-11-01T12:58:53Z
So, there is no free way to train models in Hugging Face using free CPU option?
2024-08-13T13:19:03Z
damn you got left hanging