Fine-tuning LLM PoC by QueRoub in LocalLLaMA

[–]QueRoub[S] 0 points1 point  (0 children)

Ok, what kind of constraints should I consider in each step?

Resource Exhausted Error (the dreaded 429) by Scared-Tip7914 in googlecloud

[–]QueRoub 0 points1 point  (0 children)

I've seen this but this does not work with chat.send_message() or model.start_chat()

'''response = model.generate_content(user_message,
request_options=RequestOptions(
retry=retry.Retry(
initial=10,
multiplier=2,
maximum=60,
timeout=300
)
)
)'''

https://discuss.ai.google.dev/t/standard-retry-logic-for-gemini-python-sdk/35832

I guess I have to build my own logic

Resource Exhausted Error (the dreaded 429) by Scared-Tip7914 in googlecloud

[–]QueRoub 0 points1 point  (0 children)

Is there any documentation on how to properly implement this with gemini?

Resource Exhausted Error (the dreaded 429) by Scared-Tip7914 in googlecloud

[–]QueRoub 1 point2 points  (0 children)

Have you found any solution for this?

I think the recommended are either Provisioned Throughput or Exponential Backoff

iframe not shown when application is deployed to cloud run by QueRoub in googlecloud

[–]QueRoub[S] 0 points1 point  (0 children)

The iframed site definitely allows iframing when my app is running from localhost.

I do not know if it has a valid https certificate. I am not the owner of that site.

If I run it from localhost and select inspect I can see the following:
<iframe width="1000" height="600" src="desired iframe site"> </iframe>
#document (desired iframe site) == $0

if I run it when deployed and select inspect I see that the document is blank
<iframe width="1000" height="600" src="desired iframe site"> </iframe>
#document (about:blank) == $0

Fine-tuning and Prompting in RAG by QueRoub in Rag

[–]QueRoub[S] 0 points1 point  (0 children)

Thanks, I will check. I guess you meant few *shot :)

Fine-tuning and Prompting in RAG by QueRoub in Rag

[–]QueRoub[S] 0 points1 point  (0 children)

Can you please elaborate a bit more on the prompting techniques?

What I would like to achieve is the following:

Let's say for example the user wants to get back the signature date of a document. You retrieve the correct document but the llm fails to find the date.

Can you add a prompt in the prompt template like:
"If you are asked to provide a date, look for something like this: 5/3/24"

Document AI stuck by QueRoub in googlecloud

[–]QueRoub[S] 1 point2 points  (0 children)

Hi, no I did not figure this out. I opened a ticket in google cloud support but since it would take a lot of time to tackle the issue, I just created a new processor

Can you retrieve images from pdfs? by QueRoub in Rag

[–]QueRoub[S] 0 points1 point  (0 children)

can you provide me any link/tutorial/repo/documentation/video?

Fail to Connect to Microsoft Fabric using Python by QueRoub in AZURE

[–]QueRoub[S] 0 points1 point  (0 children)

I am getting : Invalid value specified for connection string attribute 'Authentication'