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AIGUYCONTENT
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New activity in TheDrummer/Moistral-11B-v3 19 days ago

WAR ON MINISTRATIONS

11
12
#1 opened about 1 year ago by
TheDrummer
New activity in mradermacher/model_requests 6 months ago

Nemotron 51B

15
#436 opened 6 months ago by
AIGUYCONTENT

Q6_K vs. Q5_K_L

3
#6 opened 6 months ago by
AIGUYCONTENT

Prompt format

3
#3 opened 7 months ago by
AIGUYCONTENT
New activity in nvidia/NVLM-D-72B 7 months ago

GGUF wen?

5
#3 opened 7 months ago by
AIGUYCONTENT
replied to mlabonne's post 8 months ago
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BTW..I think you're on to something with what you did to this model. However, I'm still learning about LLMs and cannot offer any advice.

If it's possible, can you somehow make future models follow instructions more carefully?

replied to mlabonne's post 8 months ago
replied to mlabonne's post 8 months ago
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Thanks but can you modify the html? That was not intentional for my message to you. Here is the HTML modified so HuggingFace will not format it:

<h 2> What Will My New Blue Widget Look Like?

<h 2> Will my green widget be affected by my decision?

<h 2> Does selling a blue widget require a permit?

do you understand or have any questions?

Here is how each section (there are three of them) must be formatted:

h2 the question i provided you)

one paragraph that is 3-4 sentences in length.

</ br>

a 2nd paragraph that is 3-4 sentences in length.

<h 3> this question must build upon the question in the h2.

one paragraph that is 3-4 sentences in length.

replied to mlabonne's post 8 months ago
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I cannot share the answer because it's a blog post for a client. I have modified the three questions in the prompt to remove client info. Outside of that the prompt remains the same.

I think this model is good at following complex instructions. But it's not great at following simple instructions. It went off the rails and refused to modify a single sentence that contained a dependent clause.

It started to not follow my instructions when the conversation reached ~6-7k tokens in length.

Here is the modified prompt (to remove client info):

Take the below three questions and write 2 paragraphs of content that is 3-4 sentences in length for each question. Then immediately beneath the 2nd paragraph, create an H3 that contains another question. That question should build upon the question in the h2. then write 1 paragraph (3-4 sentences in length).
Do NOT add anymore html. Just identify the h2 and h3 and thatโ€™s that. Add a line break in between each paragraph for each h2.

What Will My New Blue Widget Look Like?

Will my green widget be affected by my decision?

Does selling a blue widget require a permit?

Here is how each section (there are three of them) must be formatted:

the question i provided you) one paragraph that is 3-4 sentences in length.
a 2nd paragraph that is 3-4 sentences in length.

this question must build upon the question in the h2. one paragraph that is 3-4 sentences in length.

replied to mlabonne's post 8 months ago
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Have you tested this on short form content? e.g. professional content for corporate websites?

Your BigQwen2.5-125B-Instruct self-merge solved a writing problem in the first shot. Technically it wasn't a problem...just a regular prompt that required the model to output content with certain HTML tags.

ChatGPT and all other open source models (interestingly enoughโ€”including regular Qwen 2.5 72B Q8) all failed no matter how many times they had to get it right.

reacted to MonsterMMORPG's post with ๐Ÿ”ฅ 8 months ago
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Post
4219
Trained Myself With 256 Images on FLUX โ€” Results Mind Blowing

Detailed Full Workflow

Medium article : https://medium.com/@furkangozukara/ultimate-flux-lora-training-tutorial-windows-and-cloud-deployment-abb72f21cbf8

Windows main tutorial : https://youtu.be/nySGu12Y05k

Cloud tutorial for GPU poor or scaling : https://youtu.be/-uhL2nW7Ddw

Full detailed results and conclusions : https://www.patreon.com/posts/111891669

Full config files and details to train : https://www.patreon.com/posts/110879657

SUPIR Upscaling (default settings are now perfect) : https://youtu.be/OYxVEvDf284

I used my Poco X6 Camera phone and solo taken images

My dataset is far from being ready, thus I have used so many repeating and almost same images, but this was rather experimental

Hopefully I will continue taking more shots and improve dataset and reduce size in future

I trained Clip-L and T5-XXL Text Encoders as well

Since there was too much push from community that my workflow wonโ€™t work with expressions, I had to take a break from research and use whatever I have

I used my own researched workflow for training with Kohya GUI and also my own self developed SUPIR app batch upscaling with face upscaling and auto LLaVA captioning improvement

Download images to see them in full size, the last provided grid is 50% downscaled

Workflow

Gather a dataset that has expressions and perspectives that you like after training, this is crucial, whatever you add, it can generate perfect

Follow one of the LoRA training tutorials / guides

After training your LoRA, use your favorite UI to generate images

I prefer SwarmUI and here used prompts (you can add specific expressions to prompts) including face inpainting :

https://gist.github.com/FurkanGozukara/ce72861e52806c5ea4e8b9c7f4409672

After generating images, use SUPIR to upscale 2x with maximum resemblance

Short Conclusions

Using 256 images certainly caused more overfitting than necessary

...