@Delta-Vector
I uploaded the 16Bit on this update. haven't tested it.
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Quazim0t0
AI & ML interests
the hunchback of huggingface 🔙 joined: 1-20-2025 🦥unsloth user 4️⃣ Phi User 🔨 ai hobbyist 📫 On Leaderboards Top 100-200
Recent Activity
updated
a model
about 1 hour ago
Quazim0t0/MFDOOM-14B
updated
a model
about 2 hours ago
Quazim0t0/MFGRIMM-14B
published
a model
about 2 hours ago
Quazim0t0/MFGRIMM-14B
Organizations
Quazim0t0's activity
replied to
their
post
about 6 hours ago
posted
an
update
about 6 hours ago
Post
144
Update to the Imagine side-project.
Just uploaded the 16Bit & Q4
*You may experience bugs with either the model or the Open WebUI function*
Open WebUI function: https://openwebui.com/f/quaz93/imagine_phi
Quazim0t0/Imagine-v0.5-16bit - Haven't tested
Quazim0t0/ImagineTest-v0.5-GGUF - Tested (Pictures)
Dataset: Quazim0t0/Amanita-Imagine
Small Dataset of 500+ entries, still working on it here and there when I can.
Pictures use the Open Web UI function I provided.
Just uploaded the 16Bit & Q4
*You may experience bugs with either the model or the Open WebUI function*
Open WebUI function: https://openwebui.com/f/quaz93/imagine_phi
Quazim0t0/Imagine-v0.5-16bit - Haven't tested
Quazim0t0/ImagineTest-v0.5-GGUF - Tested (Pictures)
Dataset: Quazim0t0/Amanita-Imagine
Small Dataset of 500+ entries, still working on it here and there when I can.
Pictures use the Open Web UI function I provided.
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- 1 reply
replied to
their
post
7 days ago
I'll try to get that out for you when I get a chance.
reacted to
AdinaY's
post with 🔥🚀
7 days ago
Post
436
LLaDA 🔥a 8B diffusion model by GSAI Lab Renmin University
✨Fully trained from scratch, LLaDA delivers performance on par with LLaMA3 8B
Model: GSAI-ML/LLaDA-8B-Instruct
Demo: multimodalart/LLaDA
Paper: Large Language Diffusion Models (2502.09992)
✨Fully trained from scratch, LLaDA delivers performance on par with LLaMA3 8B
Model: GSAI-ML/LLaDA-8B-Instruct
Demo: multimodalart/LLaDA
Paper: Large Language Diffusion Models (2502.09992)
reacted to
ZennyKenny's
post with 👍
8 days ago
Post
1858
I've spent most of time working with AI on user-facing apps like Chatbots and TextGen, but today I decided to work on something that I think has a lot of applications for Data Science teams:
ZennyKenny/comment_classification
This Space supports uploading a user CSV and categorizing the fields based on user-defined categories. The applications of AI in production are truly endless. 🚀
This Space supports uploading a user CSV and categorizing the fields based on user-defined categories. The applications of AI in production are truly endless. 🚀
posted
an
update
8 days ago
Post
2201
Debugging Tags:
Imagine, Associated Thoughts, Dialectical Analysis, Backwards Induction, Metacognition, and Normal Thought Processes such as <think> or <begin_of_thought>
Edit: Uploaded new images w/ a Open WebUI function to organize the tags.
Open WebUI Function: https://openwebui.com/f/quaz93/imagine_phi
This Phi-4 model is part of a test project that I called Micro-Dose. My goal was to use a small dataset to activate reasoning and other cognitive processes without relying on a large dataset.
I found that this was possible with a tiny dataset of just 90 rows, specifically designed as math problems. In the initial iterations, the dataset only activated reasoning when a math-related question was asked. I then made a few changes to the dataset’s structure, including the order of information and the naming of tags. You can see the sample results in the pictures. Not really anything special, just thought I'd share.
Tweaked the dataset a bit:
Quazim0t0/Imagine-Phi-v0.2-GGUF
Quazim0t0/MicroDoseV0.2
First image shows the new tags, second shows the regular thought process and the third is the model in combination with web searches
Imagine, Associated Thoughts, Dialectical Analysis, Backwards Induction, Metacognition, and Normal Thought Processes such as <think> or <begin_of_thought>
Edit: Uploaded new images w/ a Open WebUI function to organize the tags.
Open WebUI Function: https://openwebui.com/f/quaz93/imagine_phi
This Phi-4 model is part of a test project that I called Micro-Dose. My goal was to use a small dataset to activate reasoning and other cognitive processes without relying on a large dataset.
I found that this was possible with a tiny dataset of just 90 rows, specifically designed as math problems. In the initial iterations, the dataset only activated reasoning when a math-related question was asked. I then made a few changes to the dataset’s structure, including the order of information and the naming of tags. You can see the sample results in the pictures. Not really anything special, just thought I'd share.
Tweaked the dataset a bit:
Quazim0t0/Imagine-Phi-v0.2-GGUF
Quazim0t0/MicroDoseV0.2
First image shows the new tags, second shows the regular thought process and the third is the model in combination with web searches
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- 2 replies
reacted to
lingvanex-mt's
post with 🔥👍
8 days ago
Post
3483
Dear HF Community!
Our company open-sourced machine translation models for 12 rare languages under MIT license.
You can use them freely with OpenNMT translation framework. Each model is about 110 mb and has an excellent performance, ( about 40000 characters / s on Nvidia RTX 3090 )
Download models there
https://huggingface.co/lingvanex
You can test translation quality there:
https://lingvanex.com/translate/
Our company open-sourced machine translation models for 12 rare languages under MIT license.
You can use them freely with OpenNMT translation framework. Each model is about 110 mb and has an excellent performance, ( about 40000 characters / s on Nvidia RTX 3090 )
Download models there
https://huggingface.co/lingvanex
You can test translation quality there:
https://lingvanex.com/translate/
reacted to
caelancooper's
post with 👍
15 days ago
Post
953
Hey Huggingface Community,
I'm just starting my journey. I'm here to learn and contribute as much as I can to the AI community. What happened with one of my models was I left the security permissions open for people to commit changes and contribute to the model in good faith and the opposite happened.
I'm open to all feedback you may have on my future projects. Let's keep it collegial and try to make something amazing. I always stride to make situations a win for all parties involved and would love to collaborate with anybody who's interested in innovation, optimization and new use cases for AI.
Thanks Everyone,
Caelan
I'm just starting my journey. I'm here to learn and contribute as much as I can to the AI community. What happened with one of my models was I left the security permissions open for people to commit changes and contribute to the model in good faith and the opposite happened.
I'm open to all feedback you may have on my future projects. Let's keep it collegial and try to make something amazing. I always stride to make situations a win for all parties involved and would love to collaborate with anybody who's interested in innovation, optimization and new use cases for AI.
Thanks Everyone,
Caelan
posted
an
update
20 days ago
Post
2370
My first attempt at using SmolAgents:
Quazim0t0/CSVAgent
The video attached was an example for this space.
Based on ZennyKenny's SqlAgent:
ZennyKenny/sqlAgent
You can upload a CSV file and it will automatically populate the table, then you can ask questions about the data.
Grab a sample CSV file here: https://github.com/datablist/sample-csv-files
The questions that can be asked may be limited.
_______________________
Second: Quazim0t0/TXTAgent
Created an Agent that converts a .txt file into a CSV file, then you can ask about the data and also download the CSV file that was generated.
_______________________
Third: Quazim0t0/ReportAgent
Upload Multiple TXT/DOC files to then generate a report from those files.
_______________________
Lastly: Quazim0t0/qResearch
A Research tool that uses DuckDuckGo for Web Searches, Wikipedia and tries to refine the answers in MLA Format.
Quazim0t0/CSVAgent
The video attached was an example for this space.
Based on ZennyKenny's SqlAgent:
ZennyKenny/sqlAgent
You can upload a CSV file and it will automatically populate the table, then you can ask questions about the data.
Grab a sample CSV file here: https://github.com/datablist/sample-csv-files
The questions that can be asked may be limited.
_______________________
Second: Quazim0t0/TXTAgent
Created an Agent that converts a .txt file into a CSV file, then you can ask about the data and also download the CSV file that was generated.
_______________________
Third: Quazim0t0/ReportAgent
Upload Multiple TXT/DOC files to then generate a report from those files.
_______________________
Lastly: Quazim0t0/qResearch
A Research tool that uses DuckDuckGo for Web Searches, Wikipedia and tries to refine the answers in MLA Format.
reacted to
Jaward's
post with 🔥
20 days ago
Post
3861
Finally here it is: a faster, custom, scalable GRPO trainer for smaller models with < 500M params, can train on 8gb ram cpu, also supports gpu for sanity sake (includes support for vllm + flash attention). Using smolLM2-135M/360M-instructs as ref & base models. Experience your own “aha” moment 🐳 on 8gb ram.
Code: https://github.com/Jaykef/ai-algorithms/blob/main/smollm2_360M_135M_grpo_gsm8k.ipynb
Code: https://github.com/Jaykef/ai-algorithms/blob/main/smollm2_360M_135M_grpo_gsm8k.ipynb
- 2 replies
replied to
ZennyKenny's
post
20 days ago
I thought this was interesting, so I worked on it a bit in my own space. Thought you might want to look at it, can't figure out some issues but I made some progress!
reacted to
ZennyKenny's
post with 🔥👍
20 days ago
Post
1982
Okay this is pretty crazy. Snowflake has CortexAI and Uber is already teasing QueryGPT, both of which prominently feature plain text to SQL features to query your database.
I decided to see how hard it would be to put together something similar using 🤗 smolagents. Turns out, it was pretty straightforward. I managed to get it done in London Luton airport this afternoon.
ZennyKenny/sqlAgent
I decided to see how hard it would be to put together something similar using 🤗 smolagents. Turns out, it was pretty straightforward. I managed to get it done in London Luton airport this afternoon.
ZennyKenny/sqlAgent
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- 2 replies