Fine-Tuning LLM using Local GPU and Infra

[Sree-abcprocure]

a big thanks for the LLM engine, i don't know if there's a provision for fine-tuning LLM models using local GPUs/ infrastructure . kindly help me with that.
`--------------------------------------------------------------------------
UnauthorizedError Traceback (most recent call last)
/data/MBBS_pharma/fineTuningLLAMAScienceQA.ipynb Cell 15 line 1
----> 1 response = FineTune.create(
2 model="llama-2-7b",
3 training_file=r"/data/MBBS_pharma/trainScience.csv",
4 validation_file=r"/data/MBBS_pharma/valScience.csv",
5 hyperparameters={
6 'lr':2e-4,
7 },
8 suffix='science-qa-llama'
9 )
10 run_id = response.id

File /data/MBBS_pharma/mbbsPharma/lib64/python3.9/site-packages/llmengine/fine_tuning.py:151, in FineTune.create(cls, model, training_file, validation_file, hyperparameters, wandb_config, suffix)
35 """
36 Creates a job that fine-tunes a specified model with a given dataset.
37
ref='/data/MBBS_pharma/mbbsPharma/lib64/python3.9/site-packages/llmengine/fine_tuning.py:0'>0;32m (...)
141
142 """
143 request = CreateFineTuneRequest(
144 model=model,
145 training_file=training_file,
ref='/data/MBBS_pharma/mbbsPharma/lib64/python3.9/site-packages/llmengine/fine_tuning.py:0'>0;32m (...)
...
--> 107 raise parse_error(response.status_code, response.content)
108 payload = response.json()
109 return payload

UnauthorizedError: Invalid API Key.
Output is truncated. View as a scrollable element or open in a text editor. Adjust cell output settings...`

[squeakymouse]

Hmm what are your LLM_ENGINE_BASE_PATH and SCALE_API_KEY environment variables set to? These are used by FineTune.create() to determine what URL to send requests to and what auth to provide.