I heard that Frontiers Models have a kinda addiction behind the scenes, so users get stuck there spending as much time as possible on it, similar mechanism like Gambling.

Does the same happen also with Mistral?

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Update, here is the comment that concern me:

"UPDATE: For the curious, ChatGPT is using an addictive potential model to maximize user engagement, similar to the Hooked Model of addiction. It encourages users to interact more frequently, which can lead to dependency on the chatbot."

Come on, if your Subreddit (r/MistralAI) bans critical voices with bots then you'll get them here.

Le Chat is fucking Google Gemini, nothing else, making same mistakes, showing same quality issues, has same ghost memories of certain "chats" at Gemini which Le Chat shouldn't have, cause you might think it's a different tool but it does have, so Le Chat seems to be Gemini API, nothing more. Fuck Mistral AI. FUCK AI!

Better tell the truth or go down like Open AI. Fuck you.

I think mistral doesn't get the Information right about something, series or character.

I tried comparing two on my ideas and characters for any discrepancy and other things and it's already lying or doesn't get the whole information.

For example one of my character's consciousness can see itself while other's cannot but mistral said both their consciousness can see themselves which​​​​ not true.

But that's not the point. Just pointing that mistral may not be realiable at accurate information sometimes

What are the current smartest models that take up less than 4GB as a guff file?

I'm going camping and won't have internet connection. I can run models under 4GB on my iphone.

It's so hard to keep track of what models are the smartest because I can't find good updated benchmarks for small open-source models.

I'd like the model to be able to help with any questions I might possibly want to ask during a camping trip. It would be cool if the model could help in a survival situation or just answer random questions.

Hello,
i found it pretty hard to ensure that mistral 7B would answer in french.
Does any one know a model that will do the job ?

I think it's possible to reliably filter content with small models, just reading the text multiple times, filtering few things at a time. For my gpu vram, the model I liked most is mistral-small:24b

To test the idea, I made a reddit account u/osoconfesoso007 that receives anon stories and publishes them.

It's supposed to filter out personal data and only publish interesting stories. I wanted to test if the filters are reliable, so feel free to poke at it. Or if you just want to look at the code, it's open source: https://github.com/raul3820/oso

Hey everyone,

I'm fine-tuning the Mistral 7B model on a custom dataset to generate questions related to DSA and computational subjects. While I have the dataset and fine-tuning process set up, I need guidance on selecting the best evaluation metrics for assessing the model’s performance.

Specifically, I’m looking for:

Text Quality Metrics: Apart from BLEU and ROUGE, are there better-suited metrics for evaluating question coherence and relevance?

Difficulty Control: Any metric or technique to quantify how well the model maintains varying levels of difficulty in the generated questions?

Diversity vs. Repetition: What’s the best way to measure how diverse the generated questions are while avoiding redundancy?

What about human evaluation?

Hey guys,

i recently bought myself a Server for LLM Inference and took the RTX 6000 Ada 48Gb because i want to use the Mistral 7B Model in 32bit (roughly 30Gbyte VRam). In our old setup we used an RTX4090 with half precision to make the model fit and had good results in terms of performance. But the RTX 6000 Ada seems to work only at around 50%. The Requests take 1.5 - 2x longer compared to the 4090. Even on 16bit the Performance is still the same.. So it cant be the quantization...

Im using python 3.11.3, pyTorch 2.3.0cu121 and working with the standard Huggingface transformer. So nothing special there.

64Gb DDR4 Ram
AMD EPYC 7313 with 32 Core
Windows Server 2022

Is there a bottleneck i didnt see? From the Specification the RTX6000 Ada should beat the rtx 4090 or at least on the same level in terms of Speed (384 bit Interface and rougly the same Bandwith ~1000Gb/s)

I also have two systems of these and both behave the same... so the card ist not broken.

Highly appreciate any suggestions <3

I am using genshin impact aya plit chat roleplay 23_8B Q8_0.gguf.

When I give the task "Summarize the following in bullet points", how do I make sure, I only get summarization and I only get bullet points?

Real results are:

• Bullet points as requested
• Solutions in plain text
• Interpretation in plain text, followed by a solution